Distant Speech Recognition Using a Microphone Array Network

• NAKANO Alberto Yoshihiro

  Department of Information and Computer Sciences, Toyohashi University of Technology

• NAKAGAWA Seiichi

  Department of Information and Computer Sciences, Toyohashi University of Technology

• YAMAMOTO Kazumasa

  Department of Information and Computer Sciences, Toyohashi University of Technology

抄録

In this work, spatial information consisting of the position and orientation angle of an acoustic source is estimated by an artificial neural network (ANN). The estimated position of a speaker in an enclosed space is used to refine the estimated time delays for a delay-and-sum beamformer, thus enhancing the output signal. On the other hand, the orientation angle is used to restrict the lexicon used in the recognition phase, assuming that the speaker faces a particular direction while speaking. To compensate the effect of the transmission channel inside a short frame analysis window, a new cepstral mean normalization (CMN) method based on a Gaussian mixture model (GMM) is investigated and shows better performance than the conventional CMN for short utterances. The performance of the proposed method is evaluated through Japanese digit/command recognition experiments.

収録刊行物

• IEICE Transactions on Information and Systems

  IEICE Transactions on Information and Systems E93-D (9), 2451-2462, 2010

  一般社団法人 電子情報通信学会

キーワード

• distant speech recognition
• microphone array network
• GMM-based CMN
• speaker's position and orientation estimation

詳細情報

• CRID: 1390001204377453952
• NII論文ID: 10027640401
• NII書誌ID: AA10826272
• DOI: 10.1587/transinf.e93.d.2451
• ISSN: 17451361
• ISSN: 09168532
• Web Site: http://www.jstage.jst.go.jp/article/transinf/E93.D/9/E93.D_9_2451/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • Crossref
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可