VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking

Quan Wang; Hannah Muckenhirn; Kevin Wilson; Prashant Sridhar; Zelin Wu; John Hershey; Rif A. Saurous; Ron J. Weiss; Ye Jia; Ignacio Lopez Moreno

arXiv · 1810.04826

VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking

Quan Wang·Hannah Muckenhirn·Kevin Wilson·Prashant Sridhar·Zelin Wu·John Hershey·Rif A. Saurous·Ron J. Weiss·Ye Jia·Ignacio Lopez Moreno

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Abstract

In this paper, we present a novel system that separates the voice of a target speaker from multi-speaker signals, by making use of a reference signal from the target speaker. We achieve this by training two separate neural networks: (1) A speaker recognition network that produces speaker-discriminative embeddings; (2) A spectrogram masking network that takes both noisy spectrogram and speaker embedding as input, and produces a mask. Our system significantly reduces the speech recognition WER on multi-speaker signals, with minimal WER degradation on single-speaker signals.

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BibTeX RIS

Quan Wang, Hannah Muckenhirn, Kevin Wilson, Prashant Sridhar, Zelin Wu, John Hershey, Rif A. Saurous, Ron J. Weiss, Ye Jia, Ignacio Lopez Moreno. 2019-06-19. VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking. https://arxiv.org/abs/1810.04826

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