韵律信息的频谱分布。

K W Grant, B E Walden
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引用次数: 56

摘要

节奏、重音和语调的韵律语音线索主要与强度、持续时间和基本频率的变化有关。因为这些线索利用了语音波形的时间特性,它们很可能在整个语音频谱中得到广泛的表示。为了确定不同频率区域对韵律线索识别的相对重要性,在200-6100 Hz范围内的六种过滤条件下,评估了音节数、音节重音、句子语调和短语边界位置四种韵律特征的识别。各滤波条件的articulation index (AI)权值相等,AI = 0.01;p(C)孤立词约等于0.40。听力正常的被试的结果表明,过滤条件与特定韵律特征的识别之间存在交互作用。例如,来自高频区域的信息在识别音节数和重音方面特别有用,而来自低频区域的信息则有助于识别语调模式。尽管存在这些谱上的差异,但总体而言,听众在识别韵律模式方面表现得非常好,尽管个体差异很明显。对于一些受试者,在六个过滤条件下达到了相同的性能水平。这些结果在听觉和听觉-视觉语音识别方面进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spectral distribution of prosodic information.

Prosodic speech cues for rhythm, stress, and intonation are related primarily to variations in intensity, duration, and fundamental frequency. Because these cues make use of temporal properties of the speech waveform they are likely to be represented broadly across the speech spectrum. In order to determine the relative importance of different frequency regions for the recognition of prosodic cues, identification of four prosodic features, syllable number, syllabic stress, sentence intonation, and phrase boundary location, was evaluated under six filter conditions spanning the range from 200-6100 Hz. Each filter condition had equal articulation index (AI) weights, AI = 0.01; p(C)isolated words approximately equal to 0.40. Results obtained with normally hearing subjects showed that there was an interaction between filter condition and the identification of specific prosodic features. For example, information from high-frequency regions of speech was particularly useful in the identification of syllable number and stress, whereas information from low-frequency regions was helpful in identifying intonation patterns. In spite of these spectral differences, overall listeners performed remarkably well in identifying prosodic patterns, although individual differences were apparent. For some subjects, equivalent levels of performance across the six filter conditions were achieved. These results are discussed in relation to auditory and auditory-visual speech recognition.

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