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    • 14. 发明授权
    • Confusable word detection in speech recognition
    • 语音识别中的混淆词检测
    • US5737723A
    • 1998-04-07
    • US297283
    • 1994-08-29
    • Michael Dennis RileyDavid Bjorn Roe
    • Michael Dennis RileyDavid Bjorn Roe
    • G10L15/10G10L15/18G10L15/28G10L9/00
    • G10L15/187
    • A speech recognition system may be trained with data that is independent from previous acoustics. This method of training is quicker and more cost effective than previous training methods. In training the system, after a vocabulary word is input into the system, a first set of phonemes representative of the vocabulary word is determined. Next, the first set of phonemes is compared with a second set of phonemes representative of a second vocabulary word. The first vocabulary word and the second vocabulary word are different. The comparison generates a confusability index. The confusability index for the second word is a measure of the likelihood that the second word will be mistaken as another vocabulary word, e.g., the first word, already in the system. This process may be repeated for each newly desired vocabulary word.
    • 可以用独立于先前声学的数据训练语音识别系统。 这种培训方法比以前的培训方法更快,更具成本效益。 在训练系统时,在将词汇单词输入到系统中之后,确定表示词汇单词的第一组音素。 接下来,将第一组音素与表示第二词汇单词的第二组音素进行比较。 第一个词汇单词和第二个词汇单词是不同的。 比较产生混淆指数。 第二个单词的混淆指数是​​第二个单词将被误认为已经在系统中的另一个词汇单词(例如第一个单词)的可能性的量度。 可以针对每个新期望的词汇单词重复该过程。
    • 19. 发明授权
    • Speech recognition employing a permissive recognition criterion for a
repeated phrase utterance
    • 语音识别采用重复的短语发音的允许识别标准
    • US5737724A
    • 1998-04-07
    • US695140
    • 1996-08-08
    • Bishnu Saroop AtalRaziel Haimi-CohenDavid Bjorn Roe
    • Bishnu Saroop AtalRaziel Haimi-CohenDavid Bjorn Roe
    • G10L15/00G10L15/08G10L15/10G10L15/22G10L15/28G01L5/06
    • G10L15/10G10L2015/088
    • The invention relates to a method and apparatus for speech recognition, the speech to be recognized including one or more words. Recognition is based on an analysis of a first and a second utterance. In accordance with the invention, the first 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 first 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 a first recognition criterion. The second utterance is compared to one or more models of speech associated with the most closely matching model (which may include the most closely matching model) to determine a second utterance similarity metric for each such comparison. The one or more second utterance similarity metrics are analyzed to determine whether the one or more metrics satisfies a second recognition criteria. The second utterance is recognized has the phrase corresponding to the most closely matching model of speech when the first and second recognition criteria are satisfied. The present invention has application to many problems in speech recognition including isolated word recognition and command spotting. An illustrative embodiment of the invention in the context of a cellular telephone is provided. Other embodiments are also discussed.
    • 本发明涉及用于语音识别的方法和装置,要识别的语音包括一个或多个单词。 识别是基于对第一和第二话语的分析。 根据本发明,将第一话语与一个或多个语音模型进行比较,以确定每个这样的比较的相似性度量。 基于一个或多个相似性度量来确定与第一个发音最匹配的语音模型。 分析对应于最接近匹配的语音模型的相似性度量,以确定相似性度量是否满足第一识别标准。 将第二个话语与与最接近匹配的模型(其可以包括最接近匹配的模型)相关联的一个或多个语音模型进行比较,以确定每个这样的比较的第二话语相似性度量。 分析一个或多个第二话语相似性度量以确定一个或多个度量是否满足第二识别标准。 当满足第一和第二识别标准时,第二个话语被识别具有对应于最接近匹配的语音模型的短语。 本发明可以应用于语音识别中的许多问题,包括孤立词识别和指令识别。 提供了在蜂窝式电话机上的本发明的说明性实施例。 还讨论了其他实施例。