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From the user selectable multiple thresholds value criteria for speech recognition

机译:从用户可选择的用于语音识别的多个阈值标准

摘要

A method and apparatus for speech recognition in which a single criterion or set of criteria is selected manually by the user, from plural classes of recognition criteria. The stored classes of recognition criteria include a default class optimized for an average user in normal conditions, at least one class having a probability of recognition greater than said default class, and at least one class having a probability of recognition less than said default class. Accordingly, the user may select that class of criteria which provides the best results for him or her, as measured by greater accuracy (fewer false positive detections) or fewer instances of non-rejection. An utterance is compared to one or more models of speech to determine a similarity metric for each such comparison. The model of speech which most closely matches the utterance is determined based on the one or more similarity metrics. The similarity metric corresponding to the most closely matching model of speech is analyzed to determine whether the similarity metric satisfies the criteria of the user-selected class. The present application has application to many problems in speech recognition including isolated word recognition and command spotting. Illustrative embodiments of the invention in the context of telecommunications instruments are provided. IMAGE
机译:一种用于语音识别的方法和装置,其中由用户从多种识别标准类别中手动选择单个标准或一组标准。所存储的识别标准的类别包括为普通用户在正常条件下优化的默认类别,至少一个类别的识别概率大于所述默认类别,以及至少一个类别的识别概率小于所述默认类别。相应地,用户可以选择该标准类别,该标准类别可以通过更高的准确性(更少的误报检测)或更少的不拒绝实例为他或她提供最佳结果。将话语与一个或多个语音模型进行比较以确定每个此类比较的相似性度量。基于一个或多个相似性度量来确定最接近发声的语音模型。分析与最紧密匹配的语音模型相对应的相似性度量,以确定相似性度量是否满足用户选择的类别的标准。本申请已经应用于语音识别中的许多问题,包括孤立的单词识别和命令发现。提供了在电信仪器的情况下本发明的说明性实施例。 <图像>

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