Shota Takeuchi

Hands-free speech recognition challenge for real-world speech dialogue systems

In this paper, we describe and review our recent development of hands-free speech dialogue system which is used for railway station guidance. In the application at the real railway station, robustness against reverberation and noise is the most essential issue for the dialogue system. To address the problem, we introduce two key techniques in our proposed hands-free system; (a) speech dialogue system construction with real speech database collection and language/acoustic model improvement, and (b) microphone array preprocessing using blind spatial subtraction array which can solve the reverberation-naiveness problem inherent in conventional microphone arrays. The experimental assessment of the proposed dialogue system reveals that our system can provide the recognition accuracy of more than 80% under realistic railway-station conditions.

Unknown example detection for example-based spoken dialog system

In a spoken dialog system, the example-based response generation method generates a response by searching a dialog example database for the example question most similar to an input user utterance. That method has the advantage of ease of system expansion. It requires, however, a number of utterance examples whose correct responses are labeled. In this paper, we propose an approach to reducing the system expansion cost. This approach employs a detection method that screens the unknown examples, the utterances to be added to the database with their correct responses. The experimental results show that the method can reduce the number of utterances required to be labeled while maintaining the system response accuracy improvement as well as full labeling.