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CONSISTENCY PREDICTION ON STREAMING SEQUENCE MODELS

机译:流序列模型的一致性预测

摘要

A method (600) for training a speech recognition model (200) includes receiving a set of training utterance pairs (302) each including a non-synthetic speech representation (304) and a synthetic speech representation (306) of a same corresponding utterance (106). The method also includes determining a consistent loss term (352) for the corresponding training utterance pair based on a first probability distribution (311) over possible non-synthetic speech recognition hypotheses generated for the corresponding non- synthetic speech representation and a second probability distribution (312) over possible synthetic speech recognition hypotheses generated for the corresponding synthetic speech representation. The first and second probability distributions are generated for output by the speech recognition model. The method also includes updating parameters of the speech recognition model based on the consistent loss term.
机译:用于训练语音识别模型(200)的方法(600)包括接收一组训练话语对(302),每个训练话语对(302)包括非合成语音表示(304)和相同的对应话语的合成语音表示(306)( 106)。 该方法还包括基于对相应的非合成语音表示和第二概率分布生成的可能的非合成语音识别假设,确定相应的训练话语对的一致损耗项(352)。 312)对相应的合成语音表示产生的可能的合成语音识别假设。 生成第一和第二概率分布,用于由语音识别模型输出。 该方法还包括基于一致损耗术语更新语音识别模型的参数。

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