Front-end Signal Processing for Improved Automatic Speech Recognition
Front-end Signal Processing for Improved Automatic Speech Recognition
批准号:
522072-2017
负责人:
Saucier, Antoine
金额:
$1.82万
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31
中文摘要
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英文摘要
Our partner Fluent.AI develops Automatic Speech Recognition (ASR) systems based on neural networks. Theperformance of ASR systems degrades significantly in the presence of noise. The types of noises that arerelevant occur e.g. on urban sidewalks, construction sites, factory floors or in cars (e.g. radio music orbackground conversations). The performance degradation of ASR systems is partly caused by a lack ofrobustness to noise of the data representations used in ASR. To improve the performance of our partner's ASRsystems, we propose to develop a pre-processing method that reduces noises in the speech signal before it issent to the ASR engine. Our method is based on independent component analysis.
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