Podcastle: Improvements of Speech Recognition by Using Acoustic Modeling Based on Wisdom of Crowds
نویسندگان
چکیده
1 はじめに 我々は,ポッドキャストを音声認識によって 自動的にテキスト化することで,それらをユー ザが全文検索できるだけではなく,詳細な閲覧, 編集も可能なソーシャルアノテーションシステ ム「PodCastle1)2)3)」の開発,運営を行っている. ポッドキャストは実環境の多様な音声データであ り,従来の音声認識技術では高い認識率を達成す ることは難しい.そこで PodCastleでは,多数 のユーザに認識誤りを訂正 (アノテーション)す る協力をしてもらうことで,音声認識率をシス テムの運用中に向上させる枠組みを採用してい る.こうすることで,検索サービスとしての質を 向上させるだけでなく,音声認識技術の底上げを はかることも狙っている. 本研究では,上記の枠組みの一環として,PodCastleを通じて得られる集合知,すなわちユー ザによる音声認識誤りの訂正結果を活用した音 響モデル学習について検討し,ポッドキャスト音 声認識において評価を行う.
منابع مشابه
Podcastle: collaborative training of acoustic models on the basis of wisdom of crowds for podcast transcription
This paper presents acoustic-model-training techniques for improving automatic transcription of podcasts. A typical approach for acoustic modeling is to create a task-specific corpus including hundreds (or even thousands) of hours of speech data and their accurate transcriptions. This approach, however, is impractical in podcast-transcription task because manual generation of the transcriptions...
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