Spoken Term Detection Using Phoneme Transition Network from Multiple Speech Recognizers' Outputs

• Natori Satoshi

  Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi

• Furuya Yuto

  Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi

• Nishizaki Hiromitsu

  Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi

• Sekiguchi Yoshihiro

  Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi

抄録

Spoken Term Detection (STD) that considers the out-of-vocabulary (OOV) problem has generated significant interest in the field of spoken document processing. This study describes STD with false detection control using phoneme transition networks (PTNs) derived from the outputs of multiple speech recognizers. PTNs are similar to subword-based confusion networks (CNs), which are originally derived from a single speech recognizer. Since PTN-formed index is based on the outputs of multiple speech recognizers, it is robust to recognition errors. Therefore, PTN should also be robust to recognition errors in an STD task, when compared to the CN-formed index from a single speech recognition system. Our PTN-formed index was evaluated on a test collection. The experiment showed that the PTN-based approach effectively detected OOV terms, and improved the F-measure value from 0.370 to 0.639 when compared with a baseline approach. Furthermore, we applied two false detection control parameters, one is based on the majority voting scheme. The other is a measure of the ambiguity of CN, to the calculation of detection score. By introducing these parameters, the performance of STD was found to be better (0.736 for the F-measure value) than that without any parameters (0.639).

収録刊行物

• Information and Media Technologies

  Information and Media Technologies 8 (2), 457-466, 2013

  Information and Media Technologies 編集運営会議

キーワード

• majority voting
• multiple speech recognizers
• network-based indexing
• spoken term detection

詳細情報

• CRID: 1390282680242172416
• NII論文ID: 130003366960
• DOI: 10.11185/imt.8.457
• ISSN: 18810896
• 本文言語コード: en
• データソース種別:
  • JaLC
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可