Kamm C A, Dirks D D, Carterette E C
J Acoust Soc Am. 1982 May;71(5):1211-24. doi: 10.1121/1.387770.
The effects of spectral shaping on speech recognition were investigated for hearing-impaired listeners with flat and steep audiometric configuration. Three frequency responses were tested: uniform frequency gain, high pass filtering, and a response shaped relative to each subject's loudness discomfort level curve. Speech-recognition performance was measured at four levels (from 80 to 95 dB SPL) using nonsense syllable (NST) and synthetic sentence (SSI) tests, presented against a background of "cafeteria noise." No significant differences in performance on the NST were observed between the two subject groups across all spectral shapes (frequency response) and presentation levels. On the SSI, performance of subjects with flat audiometric configuration was highest using the uniform frequency response, while performance of listeners with steep configuration was poorest for the uniform response. The recognition data were compared with predictions of relative performance using a modification of the Articulation index (AI). The AIs provided accurate estimates of relative performance across spectral shapes but were not consistent with relative performance as a function of presentation level. The results indicate that the selection of spectral shape for optimal performance is influenced by the particular speech task used to test recognition and also suggest that, with further validation, the AI may provide an objective technique for selecting optimal spectral shape.
针对听力图呈平坦型和陡峭型的听力受损听众，研究了频谱整形对言语识别的影响。测试了三种频率响应：均匀频率增益、高通滤波以及相对于每个受试者响度不适水平曲线进行整形的响应。使用无意义音节（NST）和合成句子（SSI）测试，在“自助餐厅噪声”背景下，于四个声压级（从80到95 dB SPL）测量言语识别性能。在所有频谱形状（频率响应）和呈现水平下，两个受试者组在NST上的表现均未观察到显著差异。在SSI测试中，听力图呈平坦型的受试者在使用均匀频率响应时表现最佳，而听力图呈陡峭型的听众在均匀响应时表现最差。使用修改后的清晰度指数（AI）将识别数据与相对性能预测进行比较。AI能够准确估计不同频谱形状下的相对性能，但与作为呈现水平函数的相对性能不一致。结果表明，用于测试识别的特定言语任务会影响为获得最佳性能而选择的频谱形状，并且还表明，经过进一步验证后，AI可能为选择最佳频谱形状提供一种客观技术。
