| Paper: | SP-P4.7 | ||
| Session: | Topics in Speech Understanding Systems | ||
| Time: | Tuesday, May 18, 15:30 - 17:30 | ||
| Presentation: | Poster | ||
| Topic: | Speech Processing: Spoken Language Systems and Dialog | ||
| Title: | PUBLIC SPEECH-ORIENTED GUIDANCE SYSTEM WITH ADULT AND CHILD DISCRIMINATION CAPABILITY | ||
| Authors: | Ryuichi Nisimura; Nara Institute of Science and Technology | ||
| Akinobu Lee; Nara Institute of Science and Technology | |||
| Hiroshi Saruwatari; Nara Institute of Science and Technology | |||
| Kiyohiro Shikano; Nara Institute of Science and Technology | |||
| Abstract: | Takemaru-kun system is a real world speech-oriented guidance system located at the Ikoma-city North Community Center. The system has been operated daily from November, 2002 to provide visitors a speech interface for information retrievals. This system also aims at the field test of a speech interface and collecting actual utterance data. By analyzing and evaluation of the collected utterances, necessities of flexible processing according to the user's age group are discovered. It becomes impossible to disregard the increase of child users when the system is installed in a public place. This paper proposes an automatic approach discriminating speakers between adult and child users, which is based on a statistical learning. This proposal realizes a flexible spoken dialogue to both adult and child users. As for parameter vectors in machine learning, acoustic and linguistic properties extracted from speech recognition logarithm likelihood scores are adopted to discriminate user's age group. Although GMM-based recognition uses only acoustic properties, this method can also consider linguistic properties. In the experiments with the SVM-based screening, we obtained 92.4% discrimination accuracy to the actual users' utterances. The advantage of using linguistic properties is also shown. This paper also describes an overview of the Takemaru-kun system and the data collection status via the field test. Performances of child speech recognition are evaluated using collected utterances. | ||
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