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    • 8. 发明公开
    • Learning in automatic speech recognition
    • Lernen zur Spracherkennung
    • EP1696421A2
    • 2006-08-30
    • EP06110328.9
    • 2006-02-23
    • AT&T Corp.
    • Hakkani-Tur, Dilek Z.Rahim, Mazin G.Tur, GokhanRiccardi, Giuseppe
    • G10L15/06
    • G10L15/063G10L15/07G10L15/18G10L15/26G10L2015/0638
    • Utterance data that includes at least a small amount of manually transcribed data is provided. Automatic speech recognition is performed on ones of the utterance data not having a corresponding manual transcription to produce automatically transcribed utterances. A model is trained using all of the manually transcribed data and the automatically transcribed utterances. A predetermined number of utterances not having a corresponding manual transcription are intelligently selected and manually transcribed. Ones of the automatically transcribed data as well as ones having a corresponding manual transcription are labeled. In another aspect of the invention, audio data is mined from at least one source, and a language model is trained for call classification from the mined audio data to produce a language model.
    • 提供了包括至少少量手动转录数据的语音数据。 对没有相应的手动转录的话语数据中的一个执行自动语音识别以产生自动转录的话语。 使用所有手动转录数据和自动转录的话语训练模型。 智能地选择并手动转录预定数量的不具有相应手动转录的话语。 自动转录的数据以及具有相应手动转录的数据的标签。 在本发明的另一方面,音频数据从至少一个源开始,并且语言模型被训练用于从所开采的音频数据进行呼叫分类以产生语言模型。