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Class-based word clustering for speech recognition using a three- level balanced hierarchical similarity
Class-based word clustering for speech recognition using a three- level balanced hierarchical similarity
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机译:使用三级平衡分层相似度的语音识别基于类的单词聚类
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摘要
In a word clustering apparatus for clustering words, a plurality of words is clustered to obtain a total tree diagram of a word dictionary representing a word clustering result, where the total tree diagram includes tree diagrams of an upper layer, a middle layer and a lower layer. In a speech recognition apparatus, a microphone converts an input utterance speech composed of a plurality of words into a speech signal, and a feature extractor extracts predetermined acoustic feature parameters from the converted speech signal. Then, a speech recognition controller executes a speech recognition process on the extracted acoustic feature parameters with reference to a predetermined Hidden Markov Model and the obtained total tree diagram of the word dictionary, and outputs a result of the speech recognition.
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