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    • 1. 发明授权
    • Determining and using acoustic confusability, acoustic perplexity and synthetic acoustic word error rate
    • 确定和使用声学混淆,声学困惑和合成声字错误率
    • US07219056B2
    • 2007-05-15
    • US09838449
    • 2001-04-19
    • Scott Elliot AxelrodPeder Andreas OlsenHarry William PrintzPeter Vincent de Souza
    • Scott Elliot AxelrodPeder Andreas OlsenHarry William PrintzPeter Vincent de Souza
    • G10L15/00G06F7/60
    • G10L15/01
    • Two statistics are disclosed for determining the quality of language models. These statistics are called acoustic perplexity and the synthetic acoustic word error rate (SAWER), and they depend upon methods for computing the acoustic confusability of words. It is possible to substitute models of acoustic data in place of real acoustic data in order to determine acoustic confusability. An evaluation model is created, a synthesizer model is created, and a matrix is determined from the evaluation and synthesizer models. Each of the evaluation and synthesizer models is a hidden Markov model. Once the matrix is determined, a confusability calculation may be performed. Different methods are used to determine synthetic likelihoods. The confusability may be normalized and smoothed and methods are disclosed that increase the speed of performing the matrix inversion and the confusability calculation. A method for caching and reusing computations for similar words is disclosed. Acoustic perplexity and SAWER are determined and applied.
    • 披露了两项统计资料来确定语言模型的质量。 这些统计数据被称为声学困惑和合成声学误码率(SAWER),并且它们依赖于计算单词的声学混淆性的方法。 为了确定声学混淆性,有可能用声学数据的代替代替真实的声学数据。 创建一个评估模型,创建一个合成器模型,并从评估和合成器模型中确定一个矩阵。 每个评估和合成器模型都是隐马尔可夫模型。 一旦矩阵被确定,可以执行混淆度计算。 使用不同的方法来确定合成可能性。 可混淆性可以被归一化和平滑,并且公开了增加执行矩阵求逆的速度和混合计算的方法。 公开了用于缓存和重用类似词语的计算的方法。 确定和应用声学困惑和SAWER。