Elisabetta Gerbino

Dialogos: a robust system for human-machine spoken dialogue on the telephone

This paper presents Dialogos, a real-time system for human-machine spoken dialogue on the telephone in task-oriented domains. The system has been tested in a large trial with inexperienced users and it has proved robust enough to allow spontaneous interactions both to users which get good recognition performance and to the ones which get lower scores. The robust behavior of the system has been achieved by combining the use of specific language models during the recognition phase of analysis, the tolerance toward spontaneous speech phenomena, the activity of a robust parser, and the use of pragmatic-based dialogue knowledge. This integration of the different modules allows to deal with partial or total breakdowns of the different levels of analysis. We report the field trial data of the system and the evaluation results of the overall system and of the submodules.

A robust system for human-machine dialogue in telephony-based applications

This paper presents a real-time system for human-machine spoken dialogue on the telephone in task-oriented domains. The system has been tested in a large trial with inexperienced users and it has proved robust enough to allow spontaneous interactions even for people with poor recognition performance. The robust behaviour of the system has been achieved by combining the use of specific language models during the recognition phase of analysis, the tolerance toward spontaneous speech phenomena, the activity of a robust parser, and the use of pragmatic-based dialogue knowledge. This integration of the different modules allows the system to deal with partial or total breakdowns at other levels of analysis. We report the field trial data of the system with respect to speech recognition metrics of word accuracy and sentence understanding rate, time-to-completion, time-to-acquisition of crucial parameters, and degree of success of the interactions in providing the speakers with the information they required. The evaluation data show that most of the subjects were able to interact fruitfully with the system. These results suggest that the design choices made to achieve robust behaviour are a promising way to create usable spoken language telephone systems.

Real-time linguistic analysis for continuous speech understanding

This paper describes the approach followed in the development of the linguistic processor of the continuous speech dialog system implemented at our labs. The application scenario (voice-based information retrieval service over the telephone) poses severe specifications to the system: it has to be speaker-independent, to deal with noisy and corrupted speech, and to work in real time. To cope with these types of applications requires to improve both efficiency and accuracy. At present, the system accepts telephone-quality speech (utterances referring to an electronic mailbox access, recorded through a PABX) and, in the speaker-independent configuration, it correctly understands 72% of the utterances in about twice real time. Experimental results are discussed, as obtained from an implementation of the system on a Sun SparcStation 1 using the C language.

Dialogue strategies for improving the usability of telephone human-machine communication

Interactions with spoken language systems may present breakdowns that are due to errors in the acoustic decoding of user utterances. Some of these errors have important consequences in reducing the naturalness of human-machine dialogues. In this paper we identify some typologies of recognition errors that cannot be recovered during the syntactico-semantic analysis, but that may be effectively approached at the dialogue level. We will describe how non-understanding and the effects of misrecognition are dealt with by Dialogos, a realtime spoken dialogue system that allows users to access a database of railway information by telephone. We will discuss the importance of supporting confirmation turns, and clarification and correction sub-dialogues. We will show the positive effects of robust dialogue management and dialogue state dependent language modeling, by taking into account both the recognition and understanding performance, and the success rate of dialogue transactions.

Test and evaluation of a spoken dialogue system

The development of spoken dialogue systems (SDSs) requires the definition of evaluation metrics which can assess the performance of these systems at different levels and compare various SDSs. The authors present a first test, made with naive users, on an integrated dialogue system for telephone speech access to a remote data base. They describe the system architecture as well as the goals of the test, its features, the methodology used during the evaluation, and the results obtained. The SDS is shown to be effective for providing the user with the required information. The presence of spontaneous speech phenomena is frequent with naive users. The dialogue helps the user to overcome the errors due to spontaneous speech. The use of isolated words for confirmation is useful, but partially limits the interaction friendliness.<<ETX>>

Improving speech understanding performance through feedback verification

Abstract A parser for continuous speech has to deal with lattices where the word hypotheses of the correct sentence are not usually perfectly aligned and short function words may be missing. To cope with these problems, a two-way interaction between the recognition module and the parser, called feedback verification procedure (FVP), has been investigated. The parser generates many solutions, that are fed back to the recognizer which realigns them against the acoustical data, finds the missing function words among the given candidates, and attributes them a new score. The best scoring solution is finally selected by the parser. Results on a 787-word, speaker-independent, telephone-bandwidth continuous speech recognition task are presented.