Speaker and session variability in speech processing

语音技术中的两个主要问题是说话人识别(谁在说话？)和语音识别(正在说什么？)。这些问题一直难以解决，因为语音中有许多类型的可变性。例如，由于通道和麦克风效应，说话人识别系统的性能下降，需要仔细建模以区分这些干扰效应和语音信号中对区分说话人有用的方面。另一方面，在语音识别中，说话人之间的差异被认为是一种滋扰，唯一真正感兴趣的类型的差异是语音差异。这项建议涉及开发新的统计方法，使用我称为说话人和通道因素的隐藏变量来建模说话人和通道变化。我正在开发的技术是纯统计的，所以很难确切地说隐藏变量代表了什么，但可以合理地推测它们反映了说话人的年龄和性别、传输通道中的电噪声和普通的背景声学噪声等特征。

Two of the principal problems in speech technologyare speaker recognition (who is speaking?) and speechrecognition (what is being said?). These problemshave resisted solution because of the numerous typesof variability in speech. For example, the performance ofspeaker recognition systems degrades as a resultof channel and microphone effects and careful modelingis needed to distinguish these nuisance effects from aspectsof the speech signal which are useful in discriminatingbetween speakers. In speech recognition on the other hand,variation betweenspeakers is considered to be a nuisance and the only type of variabilitywhich is of real interest is phonetic variability.This proposal is concerned with developing newstatistical methods of modeling speaker and channel variation using`hidden variables' which I call speaker and channel factors.The techniques that I am developing are purely statistical soit is hard to say exactly what the hidden variables represent butit is reasonable to surmise that they capture features such asa speaker's age and sex, electrical noise in transmission channels andordinary background acoustic noise.