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Formant-Frequency Variation and Informational Masking of Speech by Extraneous Formants: Evidence Against Dynamic and Speech-Specific Acoustical Constraints

机译:共振峰频率变化和外来共振峰对信息的掩盖:反对动态和特定于语音的声学约束的证据

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摘要

How speech is separated perceptually from other speech remains poorly understood. Recent research indicates that the ability of an extraneous formant to impair intelligibility depends on the variation of its frequency contour. This study explored the effects of manipulating the depth and pattern of that variation. Three formants (F1+F2+F3) constituting synthetic analogues of natural sentences were distributed across the 2 ears, together with a competitor for F2 (F2C) that listeners must reject to optimize recognition (left = F1+F2C; right = F2+F3). The frequency contours of F1 − F3 were each scaled to 50% of their natural depth, with little effect on intelligibility. Competitors were created either by inverting the frequency contour of F2 about its geometric mean (a plausibly speech-like pattern) or using a regular and arbitrary frequency contour (triangle wave, not plausibly speech-like) matched to the average rate and depth of variation for the inverted F2C. Adding a competitor typically reduced intelligibility; this reduction depended on the depth of F2C variation, being greatest for 100%-depth, intermediate for 50%-depth, and least for 0%-depth (constant) F2Cs. This suggests that competitor impact depends on overall depth of frequency variation, not depth relative to that for the target formants. The absence of tuning (i.e., no minimum in intelligibility for the 50% case) suggests that the ability to reject an extraneous formant does not depend on similarity in the depth of formant-frequency variation. Furthermore, triangle-wave competitors were as effective as their more speech-like counterparts, suggesting that the selection of formants from the ensemble also does not depend on speech-specific constraints.
机译:如何将语音与其他语音在知觉上分离开,仍然知之甚少。最近的研究表明,外来共振峰削弱清晰度的能力取决于其频率轮廓的变化。这项研究探索了操纵这种变化的深度和模式的效果。构成自然句子的合成类似物的三个共振峰(F1 + F2 + F3)分布在两个耳朵上,另外还有F2(F2C)的竞争者,听众必须拒绝该竞争者以优化识别(左= F1 + F2C;右= F2 + F3 )。 F1-F3的频率轮廓分别缩放到其自然深度的50%,对清晰度的影响很小。通过将F2的频率轮廓反转为其几何均值(似语音形式)或使用与平均变化率和深度相匹配的规则和任意频率轮廓(三角波,似似语音形式)来创建竞争对手对于倒F2C。增加竞争对手通常会降低清晰度;这种减少取决于F2C变化的深度,对于100%深度最大,对于50%深度为中间,对于0%深度(恒定)F2C最小。这表明竞争对手的影响取决于频率变化的整体深度,而不是相对于目标共振峰的深度。没有调整(即对于50%的情况,清晰度没有最低要求)表明拒绝多余共振峰的能力不取决于共振峰频率变化深度的相似性。此外,三角波竞争者的效果与语音类似的竞争者一样有效,这表明从合奏中选择共振峰也并不取决于语音特定的约束。

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