arXiv Computer Science
arXiv Computer Science
4 years ago

Personal VAD: Speaker-Conditioned Voice Activity Detection. (arXiv:1908.04284v3 [eess.AS] UPDATED)

Shaojin Ding, Quan Wang, Shuo-yiin Chang, Li Wan, Ignacio Lopez Moreno
In this paper, we propose "personal VAD", a system to detect the voice activity of a target speaker at the frame level. This system is useful for gating the inputs to a streaming on-device speech recognition system, such that it only triggers for the target user, which helps reduce the computational cost and battery consumption. We achieve this by training a VAD-alike neural network that is conditioned on the target speaker embedding or the speaker verification score. For each frame, personal VAD outputs the probabilities for three classes: non-speech, target speaker speech, and non-target speaker speech. Under our optimal setup, we are able to train a model with 130K parameters that outperforms a baseline system where individually trained standard VAD and speaker recognition networks are combined to perform the same task.

Publisher URL: http://arxiv.org/abs/1908.04284

DOI: arXiv:1908.04284v3

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