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Robustness to environmental changes of a context dependent speech recognizer

机译:上下文相关语音识别器对环境变化的鲁棒性

摘要

An apparatus to improve robustness to environmental changes of a context dependent speech recognizer for an application, that includes a training database to store sounds for speech recognition training, a dictionary to store words supported by the speech recognizer, and a speech recognizer training module to train a set of one or more multiple state Hidden Markov Models (HMMs) with use of the training database and the dictionary. The speech recognizer training module performs a non-uniform state clustering process on each of the states of each HMM, which includes using a different non-uniform cluster threshold for at least some of the states of each HMM to more heavily cluster and correspondingly reduce a number of observation distributions for those of the states of each HMM that are less empirically affected by one or more contextual dependencies.
机译:一种用于提高针对应用的上下文相关语音识别器的环境变化的鲁棒性的设备,该设备包括用于存储语音识别训练的声音的训练数据库,用于存储语音识别器支持的单词的词典以及用于训练的语音识别器训练模块使用训练数据库和字典的一组一个或多个多状态隐马尔可夫模型(HMM)。语音识别器训练模块对每个HMM的每个状态执行非均匀状态聚类过程,包括对每个HMM的至少某些状态使用不同的非均匀聚类阈值,以更重地聚类并相应地减少每个HMM状态的观察分布的数量,这些观察分布受一个或多个上下文相关性的经验影响较小。

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