Saba Juliana N, Hansen John H L
Center for Robust Speech Systems-Cochlear Implant Processing Lab, University of Texas at Dallas, 800 West Campbell Road, Richardson, Texas 75080, USA.
J Acoust Soc Am. 2022 Feb;151(2):1007. doi: 10.1121/10.0009377.
Natural compensation of speech production in challenging listening environments is referred to as the Lombard effect (LE). The resulting acoustic differences between neutral and Lombard speech have been shown to provide intelligibility benefits for normal hearing (NH) and cochlear implant (CI) listeners alike. Motivated by this outcome, three LE perturbation approaches consisting of pitch, duration, formant, intensity, and spectral contour modifications were designed specifically for CI listeners to combat speech-in-noise performance deficits. Experiment 1 analyzed the effects of loudness, quality, and distortion of approaches on speech intelligibility with and without formant-shifting. Significant improvements of +9.4% were observed in CI listeners without the formant-shifting approach at +5 dB signal-to-noise ratio (SNR) large-crowd-noise (LCN) when loudness was controlled, however, performance was found to be significantly lower for NH listeners. Experiment 2 evaluated the non-formant-shifting approach with additional spectral contour and high pass filtering to reduce spectral smearing and decrease distortion observed in Experiment 1. This resulted in significant intelligibility benefits of +30.2% for NH and +21.2% for CI listeners at 0 and +5 dB SNR LCN, respectively. These results suggest that LE perturbation may be useful as front-end speech modification approaches to improve intelligibility for CI users in noise.
在具有挑战性的聆听环境中，语音产生的自然补偿被称为伦巴德效应（LE）。研究表明，中性语音和伦巴德语音之间产生的声学差异，能为正常听力（NH）者和人工耳蜗（CI）使用者带来可懂度方面的益处。受此结果启发，专门为CI使用者设计了三种伦巴德效应微扰方法，包括音高、时长、共振峰、强度和频谱轮廓修改，以解决噪声环境下语音表现不佳的问题。实验1分析了有无共振峰偏移时，方法的响度、音质和失真对语音可懂度的影响。在控制响度的情况下，CI使用者在+5 dB信噪比（SNR）大人群噪声（LCN）环境中，无共振峰偏移方法时可懂度显著提高了9.4%，然而，NH使用者的表现则显著更低。实验2评估了无共振峰偏移方法，并增加了频谱轮廓和高通滤波，以减少实验1中观察到的频谱模糊并降低失真。这分别为NH使用者和CI使用者在0和+5 dB SNR LCN环境下带来了30.2%和21.2%的显著可懂度提升。这些结果表明，伦巴德效应微扰作为前端语音修改方法，可能有助于提高CI使用者在噪声环境中的可懂度。
