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Deterministic Annealing Based Training Algorithm for Bayesian Speech Recognition
https://nitech.repo.nii.ac.jp/records/3402
https://nitech.repo.nii.ac.jp/records/3402a5c59fa3-5953-4f83-a255-bd39bcfc726b
名前 / ファイル | ライセンス | アクション |
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本文_fulltext (245.9 kB)
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Item type | 会議発表論文 / Conference Paper(1) | |||||
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公開日 | 2012-11-07 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Deterministic Annealing Based Training Algorithm for Bayesian Speech Recognition | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
資源タイプ | conference paper | |||||
著者 |
Shiota, Sayaka
× Shiota, Sayaka× Hashimoto, Kei× 南角, 吉彦× Tokuda, Keiichi |
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著者別名 | ||||||
言語 | en | |||||
言語 | ja | |||||
言語 | ja-Kana | |||||
姓名 | Nankaku, Yoshihiko | |||||
言語 | en | |||||
姓名 | 南角, 吉彦 | |||||
言語 | ja | |||||
姓名 | ナンカク, ヨシヒコ | |||||
言語 | ja-Kana | |||||
著者別名 | ||||||
言語 | en | |||||
言語 | ja | |||||
言語 | ja-Kana | |||||
姓名 | Tokuda, Keiichi | |||||
言語 | en | |||||
姓名 | 徳田, 恵一 | |||||
言語 | ja | |||||
姓名 | トクダ, ケイイチ | |||||
言語 | ja-Kana | |||||
書誌情報 |
INTERSPEECH 2009 10th Annual Conference of the International Speech Communication Association p. 680-683, 発行日 2009 |
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出版者 | ||||||
出版者 | International Speech Communication Association | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | This paper proposes a deterministic annealing based training algorithmfor Bayesian speech recognition. The Bayesian methodis a statistical technique for estimating reliable predictive distributionsby marginalizing model parameters. However, the localmaxima problem in the Bayesian method is more serious thanin the ML-based approach, because the Bayesian method treatsnot only state sequences but also model parameters as latentvariables. The deterministic annealing EM (DAEM) algorithmhas been proposed to improve the local maxima problem in theEM algorithm, and its effectiveness has been reported in HMMbasedspeech recognition using ML criterion. In this paper, theDAEM algorithm is applied to Bayesian speech recognition torelax the local maxima problem. Speech recognition experimentsshow that the proposed method achieved a higher performancethan the conventional methods. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | Brighton, United KingdomSeptember 6-10, 2009 | |||||
関連サイト | ||||||
識別子タイプ | URI | |||||
関連識別子 | http://www.isca-speech.org/archive/interspeech_2009/i09_0680.html | |||||
関連名称 | http://www.isca-speech.org/archive/interspeech_2009/i09_0680.html | |||||
フォーマット | ||||||
内容記述タイプ | Other | |||||
内容記述 | application/pdf |