Spoken Language Models and Dialog 4
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1: ICSLP'98 Proceedings
Keynote SpeechesText-To-Speech Synthesis 1Spoken Language Models and Dialog 1Prosody and Emotion 1Hidden Markov Model Techniques 1Speaker and Language Recognition 1Multimodal Spoken Language Processing 1Isolated Word RecognitionRobust Speech Processing in Adverse Environments 1Spoken Language Models and Dialog 2Articulatory Modelling 1Talking to Infants, Pets and LoversRobust Speech Processing in Adverse Environments 2Spoken Language Models and Dialog 3Speech Coding 1Articulatory Modelling 2Prosody and Emotion 2Neural Networks, Fuzzy and Evolutionary Methods 1Utterance Verification and Word Spotting 1 / Speaker Adaptation 1Text-To-Speech Synthesis 2Spoken Language Models and Dialog 4Human Speech Perception 1Robust Speech Processing in Adverse Environments 3Speech and Hearing Disorders 1Prosody and Emotion 3Spoken Language Understanding Systems 1Signal Processing and Speech Analysis 1Spoken Language Generation and Translation 1Spoken Language Models and Dialog 5Segmentation, Labelling and Speech Corpora 1Multimodal Spoken Language Processing 2Prosody and Emotion 4Neural Networks, Fuzzy and Evolutionary Methods 2Large Vocabulary Continuous Speech Recognition 1Speaker and Language Recognition 2Signal Processing and Speech Analysis 2Prosody and Emotion 5Robust Speech Processing in Adverse Environments 4Segmentation, Labelling and Speech Corpora 2Speech Technology Applications and Human-Machine Interface 1Large Vocabulary Continuous Speech Recognition 2Text-To-Speech Synthesis 3Language Acquisition 1Acoustic Phonetics 1Speaker Adaptation 2Speech Coding 2Hidden Markov Model Techniques 2Multilingual Perception and Recognition 1Large Vocabulary Continuous Speech Recognition 3Articulatory Modelling 3Language Acquisition 2Speaker and Language Recognition 3Text-To-Speech Synthesis 4Spoken Language Understanding Systems 4Human Speech Perception 2Large Vocabulary Continuous Speech Recognition 4Spoken Language Understanding Systems 2Signal Processing and Speech Analysis 3Human Speech Perception 3Speaker Adaptation 3Spoken Language Understanding Systems 3Multimodal Spoken Language Processing 3Acoustic Phonetics 2Large Vocabulary Continuous Speech Recognition 5Speech Coding 3Language Acquisition 3 / Multilingual Perception and Recognition 2Segmentation, Labelling and Speech Corpora 3Text-To-Speech Synthesis 5Spoken Language Generation and Translation 2Human Speech Perception 4Robust Speech Processing in Adverse Environments 5Text-To-Speech Synthesis 6Speech Technology Applications and Human-Machine Interface 2Prosody and Emotion 6Hidden Markov Model Techniques 3Speech and Hearing Disorders 2 / Speech Processing for the Speech and Hearing Impaired 1Human Speech ProductionSegmentation, Labelling and Speech Corpora 4Speaker and Language Recognition 4Speech Technology Applications and Human-Machine Interface 3Utterance Verification and Word Spotting 2Large Vocabulary Continuous Speech Recognition 6Neural Networks, Fuzzy and Evolutionary Methods 3Speech Processing for the Speech-Impaired and Hearing-Impaired 2Prosody and Emotion 72: SST Student Day
SST Student Day - Poster Session 1SST Student Day - Poster Session 2Author Index
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SQEL: A Multilingual and Multifunctional Dialogue System
Authors:
Maria Aretoulaki, FORWISS (Bavarian Research Centre for Knowledge-Based Systems) (Germany)
Stefan Harbeck, University of Erlangen (Germany)
Florian Gallwitz, University of Erlangen (Germany)
Elmar Nöth, University of Erlangen (Germany)
Heinrich Niemann, University of Erlangen & FORWISS (Germany)
Jozef Ivanecky, Technical University of Kosice (Slovak Republic)
Ivo Ipsic, University of Ljubljana (Slovenia)
Nikola Pavesic, University of Ljubljana (Slovenia)
Vaclav Matousek, University of West Bohemia in Pilsen (Czech Republic)
Page (NA) Paper number 329
Abstract:
Within the EC SQEL project, the German EVAR spoken dialogue system has been extended to handle four different languages and domains: German, Slovak, and Czech (national train connections), and Slovenian (European flights). The SQEL demonstrator can also access databases on the WWW, enabling users without an internet connection to meet their information needs by just using the phone. When the system starts up, the caller is free to use any of the implemented languages. A multilingual word recognizer implicitly identifies the language, which is then associated with the appropriate domain and database. For the remainder of the dialogue, the corresponding monolingual recognizer is employed. The existence of language-independent parameters (e.g. goal/source location) has meant that porting the system to a new language does not involve an extensive restructuring of the interpretation process within the Dialogue Manager. This is sufficiently flexible to switch between the different domains and languages.
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Semi-Automated Incremental Prototyping of Spoken Dialog Systems
Authors:
Stefan Kaspar, University of New South Wales (Australia)
Achim Hoffmann, University of New South Wales (Australia)
Page (NA) Paper number 651
Abstract:
Cost-effective development and widespread deployment of spoken language systems is only possible if their development process is substantially supported by intelligent design tools. In this paper, we present PIA a new approach for fast prototyping of complex spoken dialog systems. Dialog structures are specified in a specialised fully declarative design language. Dialog design in PIA is considered a knowledge acquisition task, where knowledge about possible user input and the desired system reaction is incrementally derived from actual interactions. PIA strongly supports the designer to keep the fine balance between robustness of recognition and the naturalness of the dialog
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Beyond Structured Dialogues: Factoring out Grounding
Authors:
Peter A. Heeman, Oregon Graduate Institute (USA)
Michael Johnston, Oregon Graduate Institute (USA)
Justin Denney, Oregon Graduate Institute (USA)
Edward Kaiser, Oregon Graduate Institute (USA)
Page (NA) Paper number 933
Abstract:
Structured dialogue models are currently the only tools for easily building spoken dialogue systems. This approach, however, requires the dialogue designer to completely specify all dialogue behavior between the user and system, including how information is grounded between the user and the system. In this paper, we advocate factoring out the grounding behavior from structured dialogue models by using a general purpose dialogue manager that accounts for this behavior. This not only simplifies the specification of dialogue, but also allows more powerful mechanisms of grounding to be employed, which cannot be implemented within the framework of structured dialogues.