Acoustic correlates of phonetic perception

如果我们能更深入地了解这些问题， 语音识别的听觉和知觉机制。实际应用中， 知识包括人工耳蜗植入信号处理器的改进， 合成设备，开发强大的语音识别算法，以及开发训练 听力受损的扬声器。拟议的实验分为三大类。一个 本文设计了一系列实验来检验一种新的元音感知模型的有效性， 是在上一个补助期内开发的。该模型假设元音身份是由一个 模板匹配过程涉及窄带输入光谱与一组平滑的 频谱形状的模板，通过普通的语音接触来学习。进行的评价 在前一个授权期间显示，该模型能够识别元音从一个大， 具有接近人类听众的准确性的多说话者数据库。我们想把这条线延伸到 致力于解决诸如以下问题：（1）建模时间和频谱线索到元音身份的整合， (2)测试该理论对诸如语音环境、信号 周期性和频谱形状特征，如共振峰幅度关系，以及（3）结合一个 心理学上合理的标准化方案，可能会解释听者的识别能力， 具有不同声道特征的说话者的讲话。将进行第二组实验， 测量有多少语音信息通过已经被 由专门设计的语音合成算法生成，该算法仅保留语音的某些特征。 原始语音信号，而故意删除或扭曲其他线索。结果将允许推论， 我们可以从中了解到调节语音识别的潜在频谱表示的本质。一 第三条工作线旨在评估一种新的听觉频率分析理论， 在上一个补助期。该理论假设听觉频谱不是在 通过对听觉神经放电模式的分析，可以在外周而在中枢神经系统中进行。软件 将进行模拟以用于测试理论的有效性。

Numerous practical and theoretical problems could be addressed if we had a deeper understanding of the auditory and perceptual mechanisms underlying phonetic recognition. Practical applications of this knowledge include improvements to cochlear implant signal processors, the improvement of speech synthesis devices, the development of robust speech recognition algorithms, and the development of training devices for hearing-impaired speakers. The proposed experiments fall into three major categories. An extensive series of experiments is designed to test the validity of a new model of vowel perception that was developed during the previous grant period. The model assumes that vowel identity is recognized by a template-matching process involving the comparison of narrow band input spectra with a set of smoothed spectral-shape templates that are learned through ordinary exposure to speech. An evaluation conducted during the previous grant period showed that the model is capable of recognizing vowels from a large, multitalker database with accuracy approaching that of human listeners. We would like to extend this line of work to address issues such as: (1) modeling the integration of temporal and spectral cues to vowel identity, (2) testing the robustness of the theory to variation in factors such as phonetic environment, signal periodicity, and spectral shape feaures such as formant amplitude relations, and (3) incorporation of a psychologically plausible normalization scheme that might account for the ability of listeners to recognize speech from talkers with diverse vocal-tract characteristics. A second set of experiments will be run which measure how much phonetic information is transmitted to listeners by speech signals that have been generated by specially designed speech synthesis algorithms that preserve only some characteristics of the original speech signal, while purposely removing or distorting other cues. The results will allow inferences to be drawn about the nature of the underlying spectral representations that mediate phonetic recognition. A third line of work is designed to evaluate a new theory of auditory frequency analysis that was developed during the previous grant period. The theory assumes that the auditory spectrum is calculated not at the periphery but in the central nervous system through an analysis of auditory nerve firing patterns. A software simulation will be developed for use in testing the validity of the theory.