Signal & Interactive Systems Lab

@article{E.2017,
title = {Cross-Language Transfer of Semantic Annotation via Targeted Crowdsourcing: Task Design and Evaluation},
author = {Stepanov A. E., Chowdhury A. S., Bayer A. O., Ghosh A., Klasinas I., Calvo M., Sanchis E. and Riccardi G.},
url = {https://sisl.disi.unitn.it/wp-content/uploads/2017/10/10.1007s10579-017-9396-5.pdf},
year = {2017},
date = {2017-01-01},
journal = {Language Resources and Evaluation, https://doi.org/10.1007/s10579-017-9396-5 , Springer, 2017},
abstract = {Modern data-driven spoken language systems (SLS) require manual semantic annotation for training spoken language understanding parsers. Multilingual porting of SLS demands significant manual effort and language resources, as this manual annotation has to be replicated. Crowdsourcing is an accessible and cost-effective alternative to traditional methods of collecting and annotating data. The application of crowdsourcing to simple tasks has been well investigated. However, complex tasks, like cross-language semantic annotation transfer, may generate low judgment agreement and/or poor performance. The most serious issue in cross-language porting is the absence of reference annotations in the target language; thus, crowd quality control and the evaluation of the collected annotations is difficult. In this paper we investigate targeted crowdsourcing for semantic annotation transfer that delegates to crowds a complex task such as segmenting and labeling of concepts taken from a domain ontology; and evaluation using source language annotation. To test the applicability and effectiveness of the crowdsourced annotation transfer we have considered the case of close and distant language pairs: Italian–Spanish and Italian–Greek. The corpora annotated via crowdsourcing are evaluated against source and target language expert annotations. We demonstrate that the two evaluation references (source and target) highly correlate with each other; thus, drastically reduce the need for the target language reference annotations.
},
keywords = {Signal Annotation and Interpretation}
}

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Mogessie A. M., Ronchetti M., Riccardi G.

Exploring the Role of Online Peer-Assessment as a Tool of Early Intervention (Article)

In Wu, Gennari, Huang, Xie and Cao Y. (eds) Emerging Technologies for Education, Lecture Notes in Computer Science, vol 10108, pp. 635-644, 2017, 2017.

(Abstract | Links | BibTeX | Tags: Interactive Systems)

Cervone A., Stepanov E. A., Celli F., and Riccardi G.

Irony Detection: from the Twittersphere to the News Space (Conference)

2017.

(Abstract | Links | BibTeX | Tags: Affective Computing, Natural Language Processing)

Singla K., Stepanov A. E., Bayer A. O., Riccardi G. and Carenini G.

Automatic Community Creation for Abstractive Spoken Summarization (Conference)

EMNLP 2017 Workshop on New Frontiers in Summarization, Copenhagen, 2017, 2017.

(Abstract | Links | BibTeX | Tags: Natural Language Processing, Speech Processing)

Chowdhury A. S., Stepanov E. A., Danieli M.. and Riccardi G.

Functions of Silences towards Information Flow in Spoken Conversation (Conference)

EMNLP 2017 Workshop on Speech-Centric Natural Language Processing, Copenhagen, 2017, 2017.

(Abstract | Links | BibTeX | Tags: Affective Computing, Speech Processing)

Bayer A. O., Stepanov A. E. and Riccardi G.

Towards End-to-End Spoken Dialogue Systems (Proceeding)

Proc. INTERSPEECH , Stockholm, 2017, 2017.

(Abstract | Links | BibTeX | Tags: Interactive Systems, Speech Processing)

Tortoreto G., Ghosh A., Stepanov E. A., Danieli M.. and Riccardi G.

Affective Behaviour Analysis of User Interactions in Support Web Group (Presentation)

01.01.2017.

(Links | BibTeX | Tags: Affective Computing)

Chowdhury A. S. and Riccardi G.

A Deep Learning Approach To Modeling Competitiveness In Spoken Conversations (Conference)

Proc. ICASSP, New Orleans, 2017, 2017.

(Abstract | Links | BibTeX | Tags: Affective Computing, Speech Processing)

Cervone A., Tortoreto G., Mezza S., Gambi E. and Riccardi G

Roving Mind: a balancing act between open–domain and engaging dialogue systems (Conference)

2017.

(Links | BibTeX | Tags: Conversational and Interactive Systems , Interactive Systems, Machine Learning, Natural Language Processing, Speech Processing)

Celli F., Stepanov A. E., Poesio M. and Riccardi G.

Predicting Brexit: Classifying Agreement is Better than Sentiment and Pollsters (Proceeding)

Proc. PEOPLES Workshop at COLING, Osaka 2016., 2016.

(Abstract | Links | BibTeX | Tags: Affective Computing, Machine Learning, Signal Annotation and Interpretation)

Alam F., Celli F., Stepanov A. E., Ghosh A. and Riccardi G.

The Social Mood of News: Self-reported Annotations to Design Automatic Mood Detection Systems (Proceeding)

Proc. PEOPLES Workshop at COLING, Osaka 2016, 2016.

(Abstract | Links | BibTeX | Tags: Affective Computing, Conversational and Interactive Systems )

Alam F. , Chowdhury S. , Danieli M. and Riccardi G.

How Interlocutors Coordinate with each other within Emotional Segments? (Proceeding)

Proc. COLING, Osaka, 2016., 2016.

(Abstract | Links | BibTeX | Tags: Affective Computing, Conversational and Interactive Systems , Discourse, Interactive Systems)

Alam F. , Danieli M.. and Riccardi G.

Can We Detect Speakers' Empathy? A Real-Life Case Study (Proceeding)

Proc. IEEE International Conference on Cognitive Infocommunications, Wrocław, 2016, 2016.

(Abstract | Links | BibTeX | Tags: Discourse, Interactive Systems)

Mogessie M., Ronchetti M. and Riccardi G.

Exploring the Role of Online Peer-Assessment as a Tool of Early Intervention (Proceeding)

Proc. International Conference on Web-based Learning, Rome, 2016., 2016.

(Abstract | Links | BibTeX | Tags: Interactive Systems)

Chowdhury S. , Stepanov A. E. and Riccardi G.

Predicting User Satisfaction from Turn-Taking in Spoken Conversations (Proceeding)

Proc. INTERSPEECH, San Francisco, 2016., 2016.

(Abstract | Links | BibTeX | Tags: Affective Computing, Conversational and Interactive Systems , Discourse, Interactive Systems, Signal Annotation and Interpretation, Speech Processing)

Mayor J. M., Ghosh A., Stepanov A. E. and Riccardi G.

HEAL-T: An Efficient PPG-based Heart-Rate And IBI Estimation Method During Physical Exercise (Proceeding)

Proc. EUSIPCO, Budapest, 2016, 2016.

(Abstract | Links | BibTeX | Tags: Health Analytics, Signal Annotation and Interpretation)

Celli F., Stepanov A. E. , Riccardi G,

Tell me who you are, I’ll tell whether you agree or disagree: Prediction of agreement/disagreement in news blogs (Proceeding)

IJCAI, Proc. Workshop on Natural Language Processing Meets Journalism, New York, 2016, 2016.

(Abstract | Links | BibTeX | Tags: Discourse)

Stepanov A. E. and Riccardi G.

The UniTN End-To-End Discourse Parser in CoNLL 2016 Shared Task (Proceeding)

Proc. CoNLL, Berlin, 2016, 2016.

(Abstract | Links | BibTeX | Tags: Discourse)

Schenk N., Chiarcos C., Donandt K., Rönnqvist S., Stepanov A. E. and Riccardi G.

Do We Really Need All Those Rich Linguistic Features? A Neural Network-Based Approach to Implicit Sense Labeling (Proceeding)

Proc. CoNLL, Berlin, 2016, 2016.

(Abstract | Links | BibTeX | Tags: Discourse, Natural Language Processing)

Mogessie M., Ronchetti M. and Riccardi G.

Predicting Student Progress from Peer-Assessment Data (Conference)

Raleigh, USA,2016, 2016.

(Abstract | Links | BibTeX | Tags: Education Analytics)

Mayor J. M., Stepanov A. E. and Riccardi G.

EEG Semantic Decoding Using Deep Neural Networks (Conference)

Workshop on Concepts, Actions and Objects, Rovereto, 2016., 2016.

(Links | BibTeX | Tags: Health Analytics, Signal Annotation and Interpretation)

Celli F., Riccardi G. and Alam F.

Multilevel Annotation of Agreement and Disagreement in Italian News Blogs (Proceeding)

Proc. Language Resources and Evaluation Conference , Portroz, 2016, 2016.

(Abstract | Links | BibTeX | Tags: Signal Annotation and Interpretation)

Chowdhury S., Stepanov A. E. and Riccardi G.

Transfer of Corpus-Specific Dialogue Act Annotation to ISO Standard: Is it worth it ? (Proceeding)

roc. Language Resources and Evaluation Conference , Portroz, 2016, 2016.

(Abstract | Links | BibTeX | Tags: Statistical Machine Translation)

Danieli M., Balamurali A. R., Stepanov A. E., Favre B., Bechet F. and Riccardi G.

Summarizing Behaviors: An Experiment on the Annotation of Call-Centre Conversations (Proceeding)

Proc. Language Resources and Evaluation Conference , Portroz, 2016, 2016.

(Abstract | Links | BibTeX | Tags: Signal Annotation and Interpretation)

Riccardi G., Stepanov A. E. and Chowdhury S.

Discourse Connective Detection in Spoken Conversations (Proceeding)

Proc. ICASSP, Shanghai, 2016, 2016.

(Abstract | Links | BibTeX | Tags: Discourse, Natural Language Processing, Speech Processing)

Danieli M., Ghosh A., Berra E., Fulcheri C., Rabbia F., Testa E., Veglio F., Riccardi G.

Automatically classifying essential arterial hypertension from physiological and daily life stress responses. (Conference)

ESH 2016 – The 26th European Meeting on Hypertension and Cardiovascular Protection, Paris, France, June 10 -13 2016., 2016.

(BibTeX | Tags: Health Analytics)

Stepanov E., Favre B., Alam F., Chowdhury S., Singla K., Trione J., Bechet F. and Riccardi G.

Automatic Summarization of Call-Center Conversations (Conference)

2015.

(Abstract | Links | BibTeX | Tags: Natural Language Processing, Speech Processing)

Stepanov E. and Riccardi G.

Sentiment Polarity Classification with Low-level Discourse-based Features (Conference)

2015.

(Links | BibTeX | Tags: Natural Language Processing, Signal Annotation and Interpretation)

Danieli M. , Riccardi G. and Alam F.

Emotion Unfolding and Affective Scenes: A Case Study in Spoken Conversations (Conference)

2015.

(Abstract | Links | BibTeX | Tags: Affective Computing, Speech Processing)

Celli F., Ghosh A., Alam F. and Riccardi G.

In the mood for Sharing Contents: Emotions, personality and interaction styles in the diffusion of news (Article)

Information Processing and Management, Nov 2015, 2015.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Signal Annotation and Interpretation)

Mogessie M, Riccardi G. and Ronchetti M.

Predicting Students’ Final Exam Scores from their Course Activities (Article)

Proc. IEEE Frontiers in Education, El Paso ( USA), 2015., 2015.

(Abstract | Links | BibTeX | Tags: Education Analytics, Machine Learning)

Danieli M., Ghosh A, Berra E., Testa E., Rabbia F., Veglio F. and Riccardi G.

Comprendere l’Ipertensione Arteriosa Essenziale A Partire da Costrutti Psicologici e Segnali Fisiologici (Conference)

2015.

(Links | BibTeX | Tags: Affective Computing, Health Analytics)

Chowdhury A, Calvo M., Ghosh A., Stepanov A. E., Bayer A. O., Riccardi G., Garcia F. and Sanchis E.

Selection and Aggregation Techniques for Crowdsourced Semantic Annotation Task (Conference)

2015.

(Abstract | Links | BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Statistical Machine Translation)

Chowdhury A,, Danieli M. and Riccardi G.

The Role of Speakers and Context in Classifying Competition in Overlapping Speech (Conference)

2015.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Signal Annotation and Interpretation)

Bayer A. O. and Riccardi G.

Deep Semantic Encodings for Language Modeling (Conference)

2015.

(Abstract | Links | BibTeX | Tags: Language Modeling, Signal Annotation and Interpretation, Speech Processing)

Favre B., Stepanov A. E., Trione J. , Bechet F. and Riccardi G.

Call Centre Conversation Summarization: A Pilot Task at Multiling 2015 (Conference)

2015.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Signal Annotation and Interpretation)

Ghosh A, Mayor Torres J.M., Danieli M. and Riccardi G.

Detection of Essential Hypertension with Physiological Signals from Wearable Devices (Conference)

2015.

(Abstract | Links | BibTeX | Tags: Health Analytics, Machine Learning, Signal Annotation and Interpretation)

Ghosh A, Danieli M. and Riccardi G.

Annotation and Prediction of Stress and Workload from Physiological and Inertial Signals (Conference)

2015.

(Abstract | Links | BibTeX | Tags: Health Analytics, Machine Learning, Signal Annotation and Interpretation)

@conference{A2015b,
title = {Annotation and Prediction of Stress and Workload from Physiological and Inertial Signals},
author = {Ghosh A, Danieli M. and Riccardi G.},
url = {https://sisl.disi.unitn.it/wp-content/uploads/2015/11/EMBC15-StressMonitoringPrediction.pdf},
year = {2015},
date = {2015-08-25},
journal = {Proc. EMBC, IEEE Conf. Engineering in Biology and Medicine Society, Milan, 2015.},
abstract = { Continuous daily stress and high workload can have negative effects on individuals’ physical and mental wellbeing. It has been shown that physiological signals may support the prediction of stress and workload. However, previous research is limited by the low diversity of signals concurring to such predictive tasks and controlled experimental design. In this paper we present 1) a pipeline for continuous and real-life acquisition of physiological and inertial signals 2) a mobile agent application for on-the-go event annotation and 3) an end-to-end signal processing and classification system for
stress and workload from diverse signal streams. We study physiological signals such as Galvanic Skin Response (GSR), Skin Temperature (ST), Inter Beat Interval (IBI) and Blood Volume Pulse (BVP) collected using a non-invasive wearable device; and inertial signals collected from accelerometer and
gyroscope sensors. We combine them with subjects’ inputs (e.g. event tagging) acquired using the agent application, and their emotion regulation scores. In our experiments we explore signal combination and selection techniques for stress and workload prediction from subjects whose signals have been recorded continuously during their daily life. The end-toend classification system is described for feature extraction, signal artifact removal, and classification. We show that a combination of physiological, inertial and user event signals provides accurate prediction of stress for real-life users and signals.},
keywords = {Health Analytics, Machine Learning, Signal Annotation and Interpretation}
}

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Stepanov E., Bayer A. O., Riccardi G.,

The UniTN Discourse Parser in CoNLL 2015 Shared Task (Conference)

2015.

(Abstract | Links | BibTeX | Tags: Discourse, Machine Learning, Natural Language Processing)

Chowdhury A, Danieli M. and Riccardi G.

Annotating and Categorizing Competition in Overlap Speech (Conference)

2015.

(Abstract | Links | BibTeX | Tags: Discourse, Natural Language Processing, Signal Annotation and Interpretation)

Vinciarelli A., Esposito A., Andre’ E., Bonin F., Chetouani M., Cohn F. J., Cristani M., Fuhrmann F., Gilmartin E., Hammal Z., Heylen D., Kaiser R., Koutsombogera M., Potamianos A., Renals S., Riccardi G., Salah A. G.

Open Challenges in Modelling, Analysis and Synthesis of Human Behaviour in Human–Human and Human–Machine Interactions (Article)

Cognitive Computation, pp. 1-17, April 2015, 2015.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Parodi S, Riccardi G, Castagnino N, Tortolina L, Maffei M, Zoppoli G, Nencioni A, Ballestrero A, Patrone F.

Systems Medicine in Oncology: Signaling-networks modeling and new generation decision-support systems (Book)

Methods Molecular Biology, Vol. 1386, Schmitz U and Wolkenhauer O (Eds): Systems Medicine, Springer Science press., 2015.

(BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation)

Celli F. and Riccardi G. and Ghosh A.

CorEA: Italian News Corpus with Emotions and Agreement (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Affective Computing, Natural Language Processing, Signal Annotation and Interpretation)

Bayer A. O. and Riccardi G.

Semantic Language Models for Automatic Speech Recognition (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Language Modeling, Natural Language Processing, Speech Processing)

Danieli M. , Riccardi G. and Alam F.

Annotation of Complex Emotions in Real-Life Dialogues: The Case of Empathy (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Affective Computing, Signal Annotation and Interpretation)

Han S., Dinarelli M., Raymond C., Lefevre F., Lehnen P., De Mori R., Moschitti A., Ney H. and Riccardi G.

Comparing Stochastic Approaches to Spoken Language Understanding in Multiple Languages (Article)

IEEE Trans. on Audio, Speech and Language Processing, vol. 19, no. 6, pp. 1569-1583, 2011, 2014.

(Abstract | Links | BibTeX | Tags: Signal Annotation and Interpretation, Speech Processing)

@article{S.2014,
title = {Comparing Stochastic Approaches to Spoken Language Understanding in Multiple Languages},
author = {Han S., Dinarelli M., Raymond C., Lefevre F., Lehnen P., De Mori R., Moschitti A., Ney H. and Riccardi G.},
url = {https://sisl.disi.unitn.it/wp-content/uploads/2014/11/IEEETSLP10-MultSLU.pdf},
year = {2014},
date = {2014-01-01},
journal = {IEEE Trans. on Audio, Speech and Language Processing, vol. 19, no. 6, pp. 1569-1583, 2011},
abstract = {One of the first steps in building a spoken language understanding (SLU) module for dialogue systems is the extraction of flat concepts out of a given word sequence, usually provided by an automatic speech recognition (ASR) system. In this paper, six different modeling approaches are investigated to tackle the task of concept tagging. These methods include classical, well-known generative and discriminative methods like Finite State Transducers (FSTs), Statistical Machine Translation (SMT), Maximum Entropy Markov Models (MEMMs), or Support Vector Machines (SVMs) as well as techniques recently applied to natural language processing such as Conditional Random Fields (CRFs) or Dynamic Bayesian Networks (DBNs). Following a detailed description of the models, experimental and comparative results are presented on three corpora in different languages and with different complexity. The French MEDIA corpus has already been exploited during an evaluation campaign and so a direct comparison with existing benchmarks is possible. Recently collected Italian and Polish corpora are used to test the robustness and portability of the modeling approaches. For all tasks, manual transcriptions as well as ASR inputs are considered. Additionally to single systems, methods for system combination are investigated. The best performing model on all tasks is based on conditional random fields. On the MEDIA evaluation corpus, a concept error rate of 12.6% could be achieved. Here, additionally to attribute names, attribute values have been extracted using a combination of a rule-based and a statistical approach. Applying system combination using weighted ROVER with all six systems, the concept error rate (CER) drops to 12.0%.},
keywords = {Signal Annotation and Interpretation, Speech Processing}
}

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Griol D., Callejas Z., Lopez-Cozar R. and Riccardi G.

A Domain-Independent Statistical Methodology for Dialog Management in Spoken Dialog Systems (Article)

Computer Speech and Language, to be published in 2014, 2014.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Riccardi G.

Towards Healthcare Personal Agents (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems )

Chowdhury S. A. and Riccardi G.

Unsupervised Recognition and Clustering of Speech Overlaps in Spoken Conversations (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Signal Annotation and Interpretation)

Chowdhury S. A., Ghosh A., Stepanov E., Bayer A. O., Riccardi G. and Klasinas I.

Cross-Language Transfer of Semantic Annotation via Targeted Crowdsourcing (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Signal Annotation and Interpretation)

Ghosh A. and Riccardi G.

Recognizing Human Activities from Smartphone Signals (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Discourse, Natural Language Processing)

Alam F. and Riccardi G.

Predicting Personality Traits using Multimodal Information (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Affective Computing)

Mogessie M., Riccardi G. and Ronchetti M.

A Web Based Peer Interaction Framework for Improved Assessment and Supervision of Students (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Education Analytics, Interactive Systems)

Stepanov E. and Riccardi G.

Towards Cross-Domain PDTB-Style Discourse Parsing (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Natural Language Processing, Signal Annotation and Interpretation)

Alam F. and Riccardi G.

Fusion of Acoustic, Linguistic and Psycholinguistic Features for Speaker Personality Traits Recognition (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Affective Computing)

Stepanov E., Riccardi G. and Bayer A. O.

The Development of the Multilingual LUNA Corpus for Spoken Language System Porting (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Natural Language Processing, Speech Processing, Statistical Machine Translation)

Ghosh S., Johansson R., Riccardi G. and Tonelli S.

Shallow Discourse Parsing with Conditional Random Fields (Conference)

2014.

(Abstract | Links | BibTeX | Tags: Discourse, Natural Language Processing)

Stepanov E., Kashkarev I., Bayer A. O., Riccardi G. and Ghosh A.

Language Style and Domain Adaptation for Cross-Language Porting (Conference)

2013.

(Abstract | Links | BibTeX | Tags: Signal Annotation and Interpretation, Statistical Machine Translation)

Bayer A. O. and Riccardi G.

On-line Adaptation of Semantic Models for Spoken Language Understanding (Conference)

2013.

(Abstract | Links | BibTeX | Tags: Machine Learning, Speech Processing)

Stepanov E. and Riccardi G.

Comparative Evaluation of Argument Extraction Algorithms in Discourse Relation Parsing (Conference)

2013.

(Abstract | Links | BibTeX | Tags: Natural Language Processing, Speech Processing)

Bayer A. O. and Riccardi G.

Instance-Based On-Line Language Model Adaptation (Conference)

2013.

(Abstract | Links | BibTeX | Tags: Machine Learning, Speech Processing)

Alam F. and Riccardi G.

Comparative Study of Speaker Personality Traits Recognition in Conversational and Broadcast News Speech (Conference)

2013.

(Abstract | Links | BibTeX | Tags: Affective Computing, Speech Processing)

Riccardi G., Ghosh A., Chowdhury S. A. and Bayer A. O.

Motivational Feedback in Crowdsourcing: a Case Study in Speech Transcriptions (Conference)

2013.

(Abstract | Links | BibTeX | Tags: Affective Computing, Conversational and Interactive Systems , Machine Learning, Signal Annotation and Interpretation)

Alam F. ,Stepanov E. and Riccardi G.

Personality Traits Recognition on Social Network - Facebook (Conference)

2013.

(Abstract | Links | BibTeX | Tags: Affective Computing, Natural Language Processing)

Dinarelli M., Moschitti A. and Riccardi G.

Discriminative Reranking for Spoken Language Understanding (Article)

IEEE Trans. on Audio, Speech and Language Processing, vol. 20, no. 2, pp. 526-539, 2012, 2012.

(Abstract | Links | BibTeX | Tags: Signal Annotation and Interpretation, Speech Processing)

Garcia F., Hurtado L. F., Segarra E., Sanchis E. and Riccardi G.

Combining Machine Translation Systems for Spoken Language Understanding Portability (Conference)

2012.

(Abstract | Links | BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Speech Processing, Statistical Machine Translation)

Bayer A. O. and Riccardi G.

Joint Language Models for Automatic Speech Recognition and Understanding (Conference)

2012.

(Abstract | Links | BibTeX | Tags: Machine Learning, Speech Processing)

Ghosh S., Riccardi G. and Johansson R.

Global Features for Shallow Discourse Parsing (Conference)

2012.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing)

Riccardi G., Cimiano P., Potamianos A., and Unger C.

Up From Limited Dialog Systems! (Conference)

2012.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems )

Ghosh S., Johansson R., Riccardi G. and Tonelli S.

Improving the Recall of a Discourse Parser by Constraint-Based Postprocessing (Conference)

2012.

(BibTeX | Tags: Discourse, Machine Learning, Natural Language Processing)

Ivanov A. V. and Riccardi G.

Kolmogorov-Smirnov Test for Feature Selection in Emotion Recognition From Speech (Conference)

2012.

(Abstract | Links | BibTeX | Tags: Affective Computing)

Stepanov E. and Riccardi G.

Detecting General Opinions from Customer Surveys (Conference)

2011.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Natural Language Processing)

Ghosh S., Tonelli S., Riccardi G. and Johansson R.

End-to-End Discourse Parser Evaluation (Conference)

2011.

(Abstract | Links | BibTeX | Tags: Discourse, Machine Learning, Natural Language Processing, Signal Annotation and Interpretation)

Moschitti A., Chu-Carroll J., Patwardhan S., Fan J. and Riccardi G.

Using Syntacting and Semantic Structural Kernels for Classifying Definition Questions in Jeopardy! (Conference)

2011.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Natural Language Processing, Signal Annotation and Interpretation)

Ivanov A. V., Riccardi G., Sporka A. J. and Franc J.

Recognition of Personality Traits from Human Spoken Conversations (Conference)

2011.

(Abstract | Links | BibTeX | Tags: Affective Computing)

Francesconi F., Ghosh A., Riccardi G., Ronchetti M. and Vagin A.

Collecting Life Logs for Experience Based Corpora (Conference)

2011.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems )

Quarteroni S., Ivanov A. V. and Riccardi G.

Simultaneous Dialog Act Segmentation and Classification from Human-Human Spoken Conversations (Conference)

2011.

(Abstract | Links | BibTeX | Tags: Natural Language Processing, Signal Annotation and Interpretation, Speech Processing)

Varges S., Riccardi G., Quarteroni S. , and Ivanov A. V.

POMDP Concept Policies and Task Structures for Hybrid Dialog Management (Conference)

2011.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems )

Ludwig B., Haecker M., Schaeller R., Zenker B., Ivanov A. V. and Riccardi G.

Tell Me Your Needs: Assistance for Public Transport Users (Conference)

2011.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems )

Quarteroni S., Gonzalez M., Riccardi G. and Varges S.

Combining User Intention and Error Modeling for Statistical Dialog Simulators (Conference)

2010.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Dinarelli M., Moschitti A. and Riccardi G.

Hypotheses Selection for Re-Ranking semantic Annotation (Conference)

2010.

(Abstract | Links | BibTeX | Tags: Signal Annotation and Interpretation)

@conference{M2010,
title = {Hypotheses Selection for Re-Ranking semantic Annotation},
author = {Dinarelli M., Moschitti A. and Riccardi G.},
url = {https://sisl.disi.unitn.it/wp-content/uploads/2014/11/SLT10-HypothSelectionReranking.pdf},
year = {2010},
date = {2010-01-01},
journal = {IEEE/ACL Workshop on Spoken Language Technology, San Francisco, 2010},
abstract = {Discriminative reranking has been successfully used for several tasks of Natural Language Processing (NLP). Recently it has been applied also to Spoken Language Understanding, imrpoving state-of-the-art for some applications. However, such proposed models can be further improved by considering: (i) a better selection of the initial nbest hypotheses to be re-ranked and (ii) the use of a strategy that decides when the reranking model should be used, i.e. in some cases only the basic approach should be applied. In this paper, we apply a semantic inconsistency metric to select the n-best hypotheses from a large set generated by an SLU basic system. Then we apply a state-of-the-art re-ranker based on the Partial Tree Kernel (PTK), which encodes SLU hypotheses in Support Vector Machines (SVM) with complex structured features. Finally, we apply a decision model based on confidence values to select between the first hypothesis provided by the basic SLU model and the first hypothesis provided by the re-ranker. We show the effectiveness of our approach presenting comparative results obtained by reranking hypotheses generated by two very different models: a simple Stochastic Language Model encoded in Finite State Machines (FSM) and a Conditional Random Field (CRF) model. We evaluate our approach on the French MEDIA corpus and on an Italian corpus acquired in the European Project LUNA. The results show a significant improvement with respect to the current state-of-the-art and previous re-ranking models. Index Terms: Spoken Language Understanding, Discriminative Reranking, Kernel Methods.},
keywords = {Signal Annotation and Interpretation}
}

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Quarteroni S. and Riccardi G.

Classifying Dialog Acts in Human-Human and Human-Machine Spoken Conversations (Conference)

2010.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Varges S., Quarteroni S., Riccardi G. and Ivanov A. V.

Investigating Clarification Strategies in a Hybrid POMDP Dialog Manager (Conference)

2010.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Gonzalez M., Quarteroni S., Riccardi G. and Varges S.

Cooperative User Models in Statistical Dialog Simulators (Conference)

2010.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Dinarelli M.,Stepanov E.,Varges S. and Riccardi G.

The LUNA Spoken Dialogue System: Beyond Utterance Classification (Conference)

2010.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Ivanov A. V., Riccardi G., Ghosh S.,Tonelli S. and Stepanov E.

Acoustic Correlates of Meaning Structure in Conversational Speech (Conference)

2010.

(Abstract | Links | BibTeX | Tags: Natural Language Processing, Speech Processing)

Ivanov A. V., Riccardi G.

Automatic Turn Segmentation in Spoken Conversations (Conference)

2010.

(Abstract | Links | BibTeX | Tags: Signal Annotation and Interpretation)

Nguyen T. T., Moschitti A. and Riccardi G.

Kernel-based Reranking for Named-Entity Extraction (Conference)

2010.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Signal Annotation and Interpretation)

Sara Tonelli S., Riccardi G., Prasad R. and Joshi A.

Annotation of Discourse Relations for Conversational Spoken Dialogs (Conference)

2010.

(Abstract | Links | BibTeX | Tags: Discourse, Natural Language Processing, Signal Annotation and Interpretation)

Varges S., Quarteroni S., Riccardi G., Ivanov A. V. and Roberti P.

Combining POMDPs trained with User Simulations and Rule-based Dialogue Management in a Spoken Dialogue System (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems )

Quarteroni S., Dinarelli M. and Riccardi G.

Ontology-Based Grounding of Spoken Language Understanding (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Varges S., Riccardi G., Quarteroni S., Ivanov A. V.

The Exploration/Exploitation Trade-Off in Reinforcement Learning for Dialogue Management (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Varges S., Riccardi G., Quarteroni S., Ivanov A. V. and Roberti P.

Leveraging POMDPs trained with User Simulations and Rule-Based Dialog Management in a SDS (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Griol D., Riccardi G. and Sanchis E.

A Statistical Dialog Manager for the LUNA Project (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Griol D., Riccardi G. and Sanchis E.

Learning the Structure of Human-Computer and Human-Human Spoken Conversations (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Quarteroni S., Riccardi G. and Dinarelli M.

What's in an Ontology for Spoken Language Understanding (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Dinarelli M., Moschitti A. and Riccardi G.

Concept Segmentation and Labeling for Conversational Speech (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Sporka A. J., Jakub F. and Riccardi G.

Can Machines Call People?- User Experience While Answering Telephone Calls Initiated by Machine (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Dinarelli M., Moschitti A. and Riccardi G.

Re-Ranking Models Based on Small Training Data for Spoken Language Understanding (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Nguyen T. T., Moschitti A. and Riccardi G.

Convolution Kernels on Constituent, Dependency and Sequential Structures for Relation Extraction (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing)

Varges S., Riccardi G., Quarteroni S., Ivanov A. V. and Roberti P.

On-Line Strategy Computation in Spoken Dialog Systems (Conference)

2009.

(Links | BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Dinarelli M., Quarteroni S., Tonelli S., Moschitti A. and Riccardi G.

Annotating Spoken Dialogs: from Speech Segments to Dialog Acts and Frame Semantics (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Natural Language Processing, Signal Annotation and Interpretation)

Dinarelli M., Moschitti A. and Riccardi G.

Re-Ranking Models For Spoken Language Understanding (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Baggia P., Cutugno F., Danieli M., Pieraccini R.

The Multisite 2009 EVALITA Spoken Dialog System Evaluation (Conference)

2009.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Signal Annotation and Interpretation)

Riccardi G., Mosca N., Roberti P. and Baggia P.

The Voice Multimodal Application Framework (Conference)

2009.

(BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Riccardi G., Baggia P. and Roberti P.

Spoken Dialog Systems: From Theory to Technology (Conference)

2009.

(BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Rodríguez K. J., Dipper S., Götze M., Poesio P., Riccardi G., Raymond C., Wisniewska J.

Standoff Coordination for Multi-Tool Annotation in a Dialogue Corpus (Conference)

2009.

(BibTeX | Tags: Machine Learning, Natural Language Processing, Signal Annotation and Interpretation)

De Mori R., Bechet F., Hakkani-Tur D., McTear M., Riccardi G. and Tur G.

Spoken Language Understanding (Article)

IEEE Signal Processing Magazine vol. 25, pp.50-58 ,2008, 2008.

(BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Bisazza A., Dinarelli M., Quarteroni S., Tonelli S., Moschitti A., Riccardi G.

Semantic Annotations For Conversational Speech: from speech transcriptions to predicate argument structures (Conference)

2008.

(BibTeX | Tags: Machine Learning, Natural Language Processing)

Dinarelli M., Moschitti A., Riccardi G.

Joint Generative And Discriminative Models For Spoken Language Understanding (Conference)

2008.

(BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Coppola B., Moschitti A., Tonelli S., Riccardi G.

Automatic FrameNet-Based Annotation of Conversational Speech (Conference)

2008.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing)

Sebastian V., Riccardi G. and Quarteroni S.

Persistent Information State in a Data-Centric Architecture (Conference)

2008.

(BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Raymond C. and Riccardi G.

Learning with Noisy Supervision for Spoken Language Understanding (Conference)

2008.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Rodríguez K., Raymond C. and Riccardi G.

Active Annotation in the LUNA Italian Corpus of Spontaneous Dialogues (Conference)

2008.

(BibTeX | Tags: Machine Learning, Natural Language Processing, Signal Annotation and Interpretation)

Varges S. and Riccardi G.

A Data-Centric Architecture for Data-Driven Spoken Dialog Systems (Conference)

2007.

(BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Moschitti A., Riccardi G. and Raymond C.

Spoken Language Understanding with Kernels for Syntactic/Semantic Structures (Conference)

2007.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Raymond C., Riccardi G.

Generative and Discriminative Algorithms for Spoken Language Understanding (Conference)

2007.

(BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Fogarolli A., Riccardi G. and Ronchetti M.

Searching for in Information in Video Lectures (Conference)

2007.

(BibTeX | Tags: Conversational and Interactive Systems )

Raymond C., Riccardi G., Rodríguez K. J. and Wisniewska J.

The LUNA Corpus: an Annotation Scheme for a Multi-domain Multi-lingual Dialogue Corpus (Conference)

2007.

(BibTeX | Tags: Machine Learning, Natural Language Processing, Signal Annotation and Interpretation)

Riccardi G. and Baggia P.

Spoken Dialog Systems: From Theory to Technology (Article)

Edizione della Normale di Pisa, 2006, 2006.

(BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Hakkani-Tur D., Riccardi G. and Tur G.

An Active Approach to spoken Language Processing (Article)

ACM Transactions on Speech and Language Processing, Vol. 3, No. 3, pp 1-31, 2006, 2006.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

@article{D.2006,
title = {An Active Approach to spoken Language Processing},
author = {Hakkani-Tur D., Riccardi G. and Tur G.},
url = {https://sisl.disi.unitn.it/wp-content/uploads/2014/11/acm-tslp-06.pdf},
year = {2006},
date = {2006-01-01},
journal = {ACM Transactions on Speech and Language Processing, Vol. 3, No. 3, pp 1-31, 2006},
abstract = {State of the art data-driven speech and language processing systems require a large amount of human intervention ranging from data annotation to system prototyping. In the traditional supervised passive approach, the system is trained on a given number of annotated data samples and evaluated using a separate test set. Then more data is collected arbitrarily, annotated, and the whole cycle is repeated. In this article, we propose the active approach where the system itself selects its own training data, evaluates itself and re-trains when necessary. We first employ active learning which aims to automatically select the examples that are likely to be the most informative for a given task. We use active learning for both selecting the examples to label and the examples to re-label in order to correct labeling errors. Furthermore, the system automatically evaluates itself using active evaluation to keep track of the unexpected events and decides on-demand to label more examples. The active approach enables dynamic adaptation of spoken language processing systems to unseen or unexpected events for nonstationary input while reducing the manual annotation effort significantly. We have evaluated the active approach with the AT&T spoken dialog system used for customer care applications. In this article, we present our results for both automatic speech recognition and spoken language understanding. Categories and Subject Descriptors: I.2.7 [Artificial Intelligence]: Natural Language Processing—Speech recognition and synthesis; I.5.1 [Pattern Recognition]: Models—Statistical General Terms: Algorithms, Languages, Performance Additional Key Words and Phrases: Passive learning, active learning, adaptive learning, unsupervised learning, active evaluation, spoken language understanding, automatic speech recognition, spoken dialog systems, speech and language processing},
keywords = {Machine Learning, Natural Language Processing, Speech Processing}
}

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Hakkani-Tur D., Bechet F., Riccardi G. and Tur G.

Beyond ASR 1-Best: Using Word Confusion Network (Article)

Computer Speech and Language, volume 20, Issue 4, pp. 495-514, 2006, 2006.

(Abstract | Links | BibTeX | Tags: Language Modeling, Speech Processing)

Gupta N., Tur G., Hakkani-Tur D., Bangalore S., Riccardi G. and Rahim M.

The AT&T Spoken Language Understanding System (Article)

IEEE Trans. on Audio, Speech and Language Processing, volume 14, Issue 1, pp. 213-22, 2006, 2006.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

@article{N.2006,
title = {The AT&T Spoken Language Understanding System},
author = {Gupta N., Tur G., Hakkani-Tur D., Bangalore S., Riccardi G. and Rahim M.},
url = {https://sisl.disi.unitn.it/wp-content/uploads/2014/11/IEEE-SAP-2005-SLU.pdf},
year = {2006},
date = {2006-01-01},
journal = {IEEE Trans. on Audio, Speech and Language Processing, volume 14, Issue 1, pp. 213-22, 2006},
abstract = {Spoken language understanding (SLU) aims at extracting meaning from natural language speech. Over the past decade, a variety of practical goal-oriented spoken dialog systems have been built for limited domains. SLU in these systems ranges from understanding predetermined phrases through fixed grammars, extracting some predefined named entities, extracting users’ intents for call classification, to combinations of users’ intents and named entities. In this paper, we present the SLU system of VoiceTone ® (a service provided by AT&T where AT&T develops, deploys and hosts spoken dialog applications for enterprise customers). The SLU system includes extracting both intents and the named entities from the users’ utterances. For intent determination, we use statistical classifiers trained from labeled data, and for named entity extraction we use rule-based fixed grammars. The focus of our work is to exploit data and to use machine learning techniques to create scalable SLU systems which can be quickly deployed for new domains with minimal human intervention. These objectives are achieved by 1) using the predicate-argument representation of semantic content of an utterance; 2) extending statistical classifiers to seamlessly integrate hand crafted classification rules with the rules learned from data; and 3) developing an active learning framework to minimize the human labeling effort for quickly building the classifier models and adapting them to changes. We present an evaluation of this system using two deployed applications of VoiceTone},
keywords = {Machine Learning, Natural Language Processing, Speech Processing}
}

Close

Coppola B., Moschitti A., Riccardi G.

Shallow Semantic Parsing for Spoken Language Understanding (Conference)

2006.

(Abstract | Links | BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Riccardi G., Ronchetti M.

NEEDLE: Next Generation Digital Libraries (Conference)

2006.

(BibTeX | Tags: Conversational and Interactive Systems )

Topkara M., Riccardi G., Hakkani-Tur D., Atallah M. J.

Natural Language Watermarking: Research Challenges and Applications (Conference)

2006.

(Abstract | Links | BibTeX | Tags: Natural Language Processing)

Riccardi G. and Hakkani-Tur D.

Grounding Emotions in Human-Machine Conversational Systems (Article)

Lecture Notes in Computer Science, Springer-Verlag, , pp. 144 – 154, 2005, 2005.

(Abstract | Links | BibTeX | Tags: Affective Computing, Conversational and Interactive Systems )

Riccardi G. and Hakkani-Tur D.

Active Learning: Theory and Applications to Automatic Speech Recognition (Article)

IEEE Trans. on Speech and Audio, vol. 13, n.4 , pp. 504-511, 2005, 2005.

(Abstract | Links | BibTeX | Tags: Machine Learning)

Potamianos A., Narayanan S. and Riccardi G.

Adaptive Categorical Understanding for Spoken Dialogue Systems' (Article)

Potamianos A., Narayanan S and Riccardi, G., 2005.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Liscombe J., Riccardi G. and Hakkani-Tur D.

Using Context to Improve Emotion Detection in Spoken Dialog Systems (Conference)

2005.

(Abstract | Links | BibTeX | Tags: Affective Computing, Speech Processing)

Hakkani-Tur D., Tur G., Riccardi G. and Kim H. K.

Error Prediction in Spoken Dialog: from Signal-to-Noise Ratio to Semantic Confidence Scores (Conference)

2005.

(BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Goffin V., Allauzen C., Bocchieri E., Hakkani-Tur D., Ljolje A., Parthasarathy S., Rahim M., Riccardi G. and Saraclar M.

The AT&T WATSON Speech Recognizer (Conference)

2005.

(BibTeX | Tags: Speech Processing)

Bechet F., Riccardi G. and Hakkani-Tur D.

Mining Spoken dialogue Corpora for system Evaluation and Modeling (Conference)

2005.

(BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Karahan M., Hakkani-Tur D., Riccardi G. and Tur G.

Combining Classifiers for Spoken Language Understanding (Conference)

2005.

(BibTeX | Tags: Machine Learning, Natural Language Processing, Speech Processing)

Hakkani-Tur D., Tur G., Rahim M. and Riccardi G.

Unsupervised and Active Learning in Automatic Speech Recognition for Call Classification (Conference)

2004.

(BibTeX | Tags: Language Modeling, Machine Learning, Speech Processing)

Tur G., Hakkani-Tur D. and Riccardi G.

Extending Boosting For Call Classification Using Word Confusion Networks (Conference)

2004.

(BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation)

Bechet F., Riccardi G. and Hakkani-Tur D.

Multi-channel Sentence Classification for Spoken Dialogue Modeling (Conference)

2003.

(BibTeX | Tags: Machine Learning, Speech Processing)

Riccardi G. and Hakkani-Tur D.

Active and Unsupervised Learning for Automatic Speech Recognition (Conference)

2003.

(BibTeX | Tags: Machine Learning)

Hakkani-Tur D. and Riccardi G.

A General Algorithm for Word Graph Decomposition (Conference)

2003.

(BibTeX | Tags: Speech Processing)

Bangalore S. and Riccardi G.

Stochastic Finite-State Models for Spoken Language Machine Translation (Article)

Machine Translation , vol 17, n. 3, pp. 165-184, 2002 (Invited paper), 2002.

(Abstract | Links | BibTeX | Tags: Statistical Machine Translation)

Gorin A., Abella A., Alonso T., Riccardi G. and Wright J.

Automated Natural Spoken Dialog (Article)

IEEE Computer, vol. 35, n.4, pp. 51-56, April, 2002 (invited paper), 2002.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Bangalore S., Murdock V., Riccardi G.

Bootstrapping Bilingual Data Using Consensus Translation for a Multilingual Instant Messaging System (Conference)

2002.

(BibTeX | Tags: Statistical Machine Translation)

Gokhan T., Wright J., Gorin A., Riccardi G., Tur H.

Improving Spoken Language Understanding Using Word Confusion Networks (Conference)

2002.

(BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Speech Processing)

Falavigna D., Gretter R. and Riccardi G.

Acoustic and Word Lattice Based Algorithms for Confidence Scores (Conference)

2002.

(BibTeX | Tags: Speech Processing)

Fabbrizio G., Dutton D., Gupta N., Hollister B., Rahim M., Riccardi G., Schapire R. and Schroeter J.

AT&T Help Desk (Conference)

2002.

(BibTeX | Tags: Conversational and Interactive Systems , Machine Learning, Speech Processing)

Rochery M., Schapire R., Rahim M., Gupta G., Riccardi G., Bangalore S., Alshawi H. and Douglas S.

Combining Prior Knowledge and Boosting for Call Classification in Spoken Language Dialogue (Conference)

2002.

(BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Speech Processing)

Tur D., Riccardi G. and Gorin A. L.

Active Learning for Automatic Speech Recognition (Conference)

2002.

(BibTeX | Tags: Machine Learning)

Bangalore S., Bordel G. and Riccardi G.

Computing Consensus Translation from Multiple Machine Translation Systems (Conference)

2002.

(BibTeX | Tags: Statistical Machine Translation)

Rahim M., Riccardi G., Saul L., Wright J., Buntschuh B. and Gorin A. L.

Robust Numeric Recognition in Spoken Language Dialogue (Article)

Speech Communication, 34, pp. 195-212, 2001, 2001.

(Abstract | Links | BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Speech Processing)

Gretter R. and Riccardi G.

On-line learning of language models with word error probability distributions (Conference)

2001.

(BibTeX | Tags: Machine Learning, Speech Processing)

Rose R. C., Yao H., Riccardi G. and Wright J. H.

Integration of Utterance Verification with Statistical Language Modeling and Spoken Language Understanding (Article)

Speech Communication, 34, pp. 321-331, 2001, 2001.

(Abstract | Links | BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Speech Processing)

Bangalore S. and Riccardi G.

A Finite-State Approach to Machine Translation (Conference)

2001.

(BibTeX | Tags: Statistical Machine Translation)

Bangalore S. and Riccardi G.

Finite-state models for lexical reordering in spoken language translation (Conference)

2000.

(BibTeX | Tags: Statistical Machine Translation)

Riccardi G.

On-line Learning of Acoustic and Lexical Units for Domain-Independent ASR (Conference)

2000.

(BibTeX | Tags: Machine Learning)

Petrovska-Delacretaz D., Gorin A. L., Riccardi G. and Wright J. H.

Detecting Acoustic Morphemes in Lattices for Spoken Language Understanding (Conference)

2000.

(BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Speech Processing)

Rahim M., Pieraccini R., Eckert W., Levin E., Di Fabbrizio G., Riccardi G., Kamm C., Narayanan S.

A Spoken Dialog System for Conference/Workshop Services (Conference)

2000.

(BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Gorin A. L., Wright J. H., Riccardi G., Abella A. and Alonso T.

Semantic information processing of spoken language (Conference)

2000.

(BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Speech Processing)

Bangalore S. and Riccardi G.

Stochastic finite-state models for spoken language machine translation,'' Proc. Workshop on Embedded Machine Translation Systems (Conference)

2000.

(BibTeX | Tags: Statistical Machine Translation)

Riccardi G. and Gorin A. L.

Spoken language adaptation over time and state in a natural spoken dialog system (Article)

IEEE Trans. on Speech and Audio, vol. 8, pp. 3-10, 2000, 2000.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Rahim M., Pieraccini R., Eckert W., Levin E., Di Fabbrizio G., Riccardi G., Lin C., Kamm C.

W99- A Spoken Dialog System for the ASRU99 Workshop (Conference)

1999.

(BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Riccardi G., Bangalore S. and Sarin P.

Learning head-dependency relations from unannotated corpora (Conference)

1999.

(BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Conkie A., Riccardi G. and Rose R. C.

Prosody recognition from speech utterances using acoustic and linguistic based models of prosodic events (Conference)

1999.

(BibTeX | Tags: Machine Learning, Speech Processing)

Potamianos A., Riccardi G. and Narayanan S.

Categorical understanding using statistical N-gram models (Conference)

1999.

(BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Speech Processing)

Rose R. C. and Riccardi G.

Automatic speech recognition using acoustic confidence conditioned language models (Conference)

1999.

(BibTeX | Tags: Speech Processing)

Gorin A. L. and Riccardi G.

Spoken language variation over time and state in a natural spoken dialog system (Conference)

1999.

(BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Rose R. C. and Riccardi G.

Modeling dysfluency and background events in ASR for a natural language understanding task (Conference)

1999.

(BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Arai K., Wright J. H., Riccardi G. and Gorin A. L.

Grammar fragment acquisition using syntactic and semantic clustering (Article)

Speech Communication, vol. 27, no. 1, Jan. 1999, 1999.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Gorin A. L., Petrovska-Delacretaz D., Riccardi G. and Wright J. H.

Learning spoken language without transcription (Conference)

1999.

(BibTeX | Tags: Machine Learning)

Rahim M., Riccardi G., Wright J., Buntschuh B. and Gorin A.

Robust automatic speech recognition in a natural spoken dialog (Conference)

1999.

(BibTeX | Tags: Language Modeling, Speech Processing)

Arai K., Wright J. H., Riccardi G. and Gorin A. L.

Grammar fragment acquisition using syntactic and semantic clustering (Conference)

1998.

(BibTeX | Tags: Machine Learning)

Riccardi G., Potamianos A. and Narayanan S.

Language model adaptation for spoken dialog systems (Conference)

1998.

(BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Riccardi G. and Gorin A. L.

Stochastic language models for speech recognition and understanding (Conference)

1998.

(BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Rose R. C., Yao H., Riccardi G. and Wright J.

Integration of utterance verification with statistical language modeling and spoken language understanding (Conference)

1998.

(BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Riccardi G. and Bangalore S.

Automatic acquisition of phrase grammars for stochastic language modeling (Conference)

1998.

(BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Arai K., Wright J., Riccardi G. and Gorin A.

Grammar fragment acquisition using syntactic and semantic clustering,'' Proc. Workshop Spoken Language Understanding & Communication (Conference)

1997.

(BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Gorin A. L., Riccardi G. and Wright J. H.

How may I help you? (Article)

Speech Communication, vol. 23, Oct. 1997, pp. 113-127., 1997.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Riccardi G., Gorin A. L., Ljolje A. and Riley M.

A spoken language system for automated call routing (Conference)

1997.

(BibTeX | Tags: Conversational and Interactive Systems , Speech Processing)

Rose R. C., Yao H., Riccardi G. and Wright J.

Integrating multiple knowledge sources for utterance verification in a large vocabulary speech understanding system (Conference)

1997.

(BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Speech Processing)

Wright J. H., Gorin A. L. and Riccardi G.

Automatic acquisition of salient grammar fragments for call-type classification (Conference)

1997.

(BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

Riccardi G., Pieraccini R. and Bocchieri E.

Stochastic automata for language modeling (Article)

Computer Speech and Language, vol. 10(4), 1996, pp. 265-293, 1996.

(Abstract | Links | BibTeX | Tags: Conversational and Interactive Systems , Language Modeling, Speech Processing)

@article{Riccardi1996,
title = {Stochastic automata for language modeling},
author = {Riccardi G., Pieraccini R. and Bocchieri E.},
url = {https://sisl.disi.unitn.it/wp-content/uploads/2014/11/csl96.pdf},
year = {1996},
date = {1996-01-01},
journal = { Computer Speech and Language, vol. 10(4), 1996, pp. 265-293},
abstract = {Stochastic language models are widely used in spoken language understanding to recognize and interpret the speech signal: the speech samples are decoded into word transcriptions by means of acoustic and syntactic models and then interpreted according to a semantic model. Both for speech recognition and understanding, search algorithms use stochastic models to extract the most likely uttered sentence and its correspondent interpretation. The design of the language models has to be effective in order to mostly constrain the search algorithms and has to be efficient to comply with the storage space limits. In this work we present the Variable N-gram Stochastic Automaton (VNSA) language model that provides a unified formalism for building a wide class of language models. First, this approach allows for the use of accurate language models for large vocabulary speech recognition by using the standard search algorithm in the one-pass Viterbi decoder. Second, the unified formalism is an effective approach to incorporate different sources of information for computing the probability of word sequences. Third, the VNSAs are well suited for those applications where speech and language decoding cascades are implemented through weighted rational transductions. The VNSAs have been compared to standard bigram and trigram language models and their reduced set of parameters does not affect by any means the performances in terms of perplexity. The design of a stochastic language model through the VNSA is described and applied to word and phrase class-based language models. The effectiveness of VNSAs has been tested within the Air Travel Information System (ATIS) task to build the language model for th},
keywords = {Conversational and Interactive Systems , Language Modeling, Speech Processing}
}

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Bocchieri E. and Riccardi G.

State tying of triphone HMM's for the 1994 AT&T ARPA ATIS recognizer (Conference)

1995.

(BibTeX | Tags: Speech Processing)

Bocchieri E., Levin E., Pieraccini R. and Riccardi G.

Understanding spontaneous speech (Article)

J. of the Italian Assoc. of Artificial Intelligence, Sept. 1995, 1995.

(BibTeX | Tags: Machine Learning, Signal Annotation and Interpretation, Speech Processing)