LINGVO/LASER: Prototyping Concept of Dialogue Information System with Spreading Knowledge

Ekštein, Kamil; Pavelka, Tomáš

doi:10.5220/0002665301590168

Proceedings of the 1st International Workshop on Natural Language Understanding and Cognitive Science 2004

DOI: 10.5220/0002665301590168

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LINGVO/LASER: Prototyping Concept of Dialogue Information System with Spreading Knowledge

Kamil Ekštein¹,

Tomáš Pavelka²

Abstract: The presented paper introduces a scalable modular prototyping concept and methodology framework for rapid development of domain-oriented dialogue information systems being developed at Laboratory of Intelligent Communication Systems (LICS). The whole system consists of two practically standalone aggregates of software modules and knowledge bases: A speech recognition and synthesis software-LASER, and a generic task-independent scalable dialogue information system-LINGVO. The article describes the architecture,… Show more

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Sentence Structure for Dialog Act Recognition in Czech

Král

Cerisara

Kleckova

et al.

2006 2nd International Conference on Information &Amp; Communication Technologies

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This paper deals with automatic dialog acts (DAs) recognition in Czech based on sentence structure. We consider the following DAs: statements, orders, yes/no questions and other questions. In our previous works, we have proposed, implemented and evaluated new approaches to automatic DAs recognition based on sentence structure and prosody. The word sequences were manually transcribed. The main goal of this paper is to evaluate the performances of our approaches when these word sequences are unknown and estimated from a speech recognizer. Our system is tested on a Czech corpus that simulates a task of train tickets reservation. When manual transcription is used, classification accuracy without and with sentence structure models is 91 %, 94 % and 95 %. The recognition accuracy reaches 96 % with prosodic combination. When word sequences are estimated from a speech recognizer, the classification score is 88 % without and 91 % and 92 % with sentence structure models. The combination with prosody gives 93 % of accuracy.

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Sentence Structure for Dialog Act Recognition in Czech

Král

Cerisara

Kleckova

et al.

2006 2nd International Conference on Information &Amp; Communication Technologies

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Combination of classifiers for automatic recognition of dialog acts

Král¹,

Cerisara²,

Kleckova³

2005

Interspeech 2005

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This paper deals with automatic dialog acts (DAs) recognition in Czech. The dialog acts are sentence-level labels that represent different states of a dialogue, depending on the application. Our work focuses on two applications: a multimodal reservation system and an animated talking head for hearing-impaired people. In that context, we consider the following DAs: statements, orders, yes/no questions and other questions. We propose to use both lexical and prosodic information for DAs recognition. The main goal of this paper is to compare different methods to combine the results of both classifiers. On a Czech corpus simulating a reservation of train tickets, the lexical information only gives about 92 % of classification accuracy, while prosody gives only about 45 % of accuracy. When both classifiers are combined with a multilayer perceptron, the lowest (lexical) word error rate further decreases by 26 %. We show that this improvement is close to the optimal one, given the correlation of the lexical and prosodic features. The other combination schemes do not outperform the lexical-only results.

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LINGVO/LASER: Prototyping Concept of Dialogue Information System with Spreading Knowledge

Cited by 2 publications

References 0 publications

Sentence Structure for Dialog Act Recognition in Czech

Sentence Structure for Dialog Act Recognition in Czech

Combination of classifiers for automatic recognition of dialog acts

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