Speech recognition in a home environment using parallel decoding with GMM-based noise modeling

Kohei Machida, Takashi Nose, Akinori Ito

研究成果: Conference contribution

抄録

In this paper, we propose a method for noise-robust speech recognition in a home environment based on noise modeling and parallel decoding. There are three basic ideas of the proposed method. First, we model the noise signals observed in the environment using a GMM. Second, we generate multiple noise-reduced signals using the mean vectors of the GMM and decode the signals in parallel. Third, we choose the best recognition result from the multiple recognition results based on the confidence score. The proposed method is very simple and straightforward, yet effective compared with simple noise reduction. The experiments proved that the proposed method is effective for not only noise signals in the database but also for those in the real home environment.

本文言語English
ホスト出版物のタイトル2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9786163618238
DOI
出版ステータスPublished - 2014 2 12
イベント2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014 - Chiang Mai, Thailand
継続期間: 2014 12 92014 12 12

出版物シリーズ

名前2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014

Other

Other2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
国/地域Thailand
CityChiang Mai
Period14/12/914/12/12

ASJC Scopus subject areas

  • 信号処理
  • 情報システム

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