Artificial bandwidth extension of narrowband speech using Gaussian Mixture Model

D. Murali Mohan, Dileep B. Karpur, M. Narayan, J. Kishore
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引用次数: 13

Abstract

Spectrum of speech signals have frequency components from 50Hz to 7 kHz (Wideband speech). However, due to historical reasons speech is band-pass filtered between 300 Hz-3.4 kHz in PSTN networks and this speech is referred to as narrowband speech. The missing bandwidth in narrow band speech contributes to speech quality and intelligibility. This paper addresses the problem of artificial bandwidth extension of narrowband speech to wideband speech. The proposed method for bandwidth extension is based on statistical recovery using Gaussian Mixture Model (GMM) for spectral envelope parameters and spectral shifting method is used for excitation extension.
基于高斯混合模型的窄带语音人工带宽扩展
语音信号频谱的频率成分从50Hz到7khz(宽带语音)。然而,由于历史原因,在PSTN网络中,语音在300 Hz-3.4 kHz之间是带通滤波的,这种语音被称为窄带语音。窄带语音中的带宽缺失会影响语音质量和清晰度。本文研究了窄带语音到宽带语音的人工带宽扩展问题。提出了基于高斯混合模型(GMM)的频谱包络参数统计恢复的带宽扩展方法,采用谱移法进行激励扩展。
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