Training Wake Word Detection with Synthesized Speech Data on Confusion
Words
- URL: http://arxiv.org/abs/2011.01460v1
- Date: Tue, 3 Nov 2020 04:06:04 GMT
- Title: Training Wake Word Detection with Synthesized Speech Data on Confusion
Words
- Authors: Yan Jia, Zexin Cai, Murong Ma, Zeqing Zhao, Xuyang Wang, Junjie Wang,
Ming Li
- Abstract summary: We investigate two data augmentation setups for training end-to-end KWS systems.
One is involving the synthesized data from a multi-speaker speech synthesis system.
The other augmentation is performed by adding random noise to the acoustic feature.
- Score: 10.97664190706851
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Confusing-words are commonly encountered in real-life keyword spotting
applications, which causes severe degradation of performance due to complex
spoken terms and various kinds of words that sound similar to the predefined
keywords. To enhance the wake word detection system's robustness on such
scenarios, we investigate two data augmentation setups for training end-to-end
KWS systems. One is involving the synthesized data from a multi-speaker speech
synthesis system, and the other augmentation is performed by adding random
noise to the acoustic feature. Experimental results show that augmentations
help improve the system's robustness. Moreover, by augmenting the training set
with the synthetic data generated by the multi-speaker text-to-speech system,
we achieve a significant improvement regarding confusing words scenario.
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