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Towards Co-Channel Speaker Separation by 2-D Demodulation of Spectrograms

机译：通过频谱图的二维解调实现共通道扬声器分离

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This paper explores a two-dimensional (2-D) processing approach for co-channel speaker separation of voiced speech. We analyze localized time- frequency regions of a narrowband spectrogram using 2-D Fourier transforms and propose a 2-D amplitude modulation model based on pitch information for single and multi-speaker content in each region. Our model maps harmonically-related speech content to concentrated entities in a transformed 2-D space, thereby motivating 2-D demodulation of the spectrogram for analysis/synthesis and speaker separation. Using a priori pitch estimates of individual speakers, we show through a quantitative evaluation: 1) Utility of the model for representing speech content of a single speaker and 2) Its feasibility for speaker separation. For the separation task, we also illustrate benefits of the model's representation of pitch dynamics relative to a sinusoidal-based separation system.

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