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Perceptual Confusions Among Consonants, Revisited: Cross-Spectral Integration of Phonetic-Feature Information and Consonant Recognition

机译:辅音中的感知混淆,重访:语音特征信息和辅音识别的跨谱整合

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摘要

The perceptual basis of consonant recognition was experimentally investigated through a study of how information associated with phonetic features (Voicing, Manner, and Place of Articulation) combines across the acoustic-frequency spectrum. The speech signals, 11 Danish consonants embedded in Consonant + Vowel + Liquid syllables, were partitioned into 3/4-octave bands (“slits”) centered at 750 Hz, 1500 Hz, and 3000 Hz, and presented individually and in two- or three-slit combinations. The amount of information transmitted (IT) was calculated from consonant- confusion matrices for each feature and slit combination. The growth of IT was measured as a function of the number of slits presented and their center frequency for the phonetic features and consonants. The IT associated with Voicing, Manner, and Consonants sums nearly linearly for two-band stimuli irrespective of their center frequency. Adding a third band increases the IT by an amount somewhat less than predicted by linear cross-spectral integration (i.e., a compressive function). In contrast, for Place of Articulation, the IT gained through addition of a second or third slit is far more than predicted by linear, cross-spectral summation. This difference is mirrored in a measure of error-pattern similarity across bands—Symmetric Redundancy. Consonants, as well as Voicing and Manner, share a moderate degree of redundancy between bands. In contrast, the cross-spectral redundancy associated with Place is close to zero, which means the bands are essentially independent in terms of decoding this feature. Because consonant recognition and Place decoding are highly correlated (correlation coefficient r2 = 0.99), these results imply that the auditory processes underlying consonant recognition are not strictly linear. This may account for why conventional cross-spectral integration speech models, such as the Articulation Index, Speech Intelligibility Index, and the Speech Transmission Index do not predict intelligibility and segment recognition well under certain conditions (e.g., discontiguous frequency bands, audio-visual speech).
机译:通过研究与语音特征(发声,方式和发音部位)相关的信息如何在整个声频谱上结合起来,实验研究了辅音识别的感知基础。语音信号是嵌入在辅音+元音+液体音节中的11个丹麦辅音,被分成以750 Hz,1500 Hz和3000 Hz为中心的3/4倍频程带(“狭缝”),并分别以两个或两个三缝组合。从每个特征和狭缝组合的辅音混淆矩阵计算出传输的信息量(IT)。 IT的增长是根据出现的缝隙数量及其中心频率(针对语音特征和辅音)的函数来衡量的。与发声,方式和辅音相关的IT几乎对两个频段的刺激进行线性求和,而不考虑其中心频率。添加第三波段将使IT的增加量比线性互谱积分(即压缩函数)所预测的增加量少一些。相反,对于“铰接位置”,通过添加第二个或第三个狭缝获得的IT远远超过线性,交叉谱求和所预测的。这种差异反映在跨频段的错误模式相似性度量(对称冗余)中。辅音以及发声和方式在频段之间共享适度的冗余度。相反,与Place相关联的交叉频谱冗余接近于零,这意味着这些频段在解码此功能方面基本上是独立的。因为辅音识别和位置解码高度相关(相关系数r2 = 0.99),所以这些结果表明辅音识别所基于的听觉过程并非严格线性。这可能可以解释为什么在某些条件下(例如,不连续的频段,视听语音),诸如清晰度指数,语音清晰度指数和语音传输指数之类的常规跨谱整合语音模型不能很好地预测清晰度和片段识别的原因)。

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