用于噪声语音训练的自动语音识别性能

A. Prodeus, Kateryna Kukharicheva
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引用次数: 7

摘要

本文比较了几种自动语音识别系统训练技术的性能。语音识别的准确性作为性能的衡量标准。采用不同类型的室内外噪声进行研究。结果表明,噪声语音训练方法优于清晰语音训练技术。研究发现,在信噪比约为5 ~ 10 dB的情况下,用带噪语音进行训练可以达到高达95 ~ 97%的识别准确率。与此同时,通过干净的语音训练可以在20…25 dB左右达到相同的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic speech recognition performance for training on noised speech
Performances of some training techniques of automatic speech recognition system are compared in this paper. Speech recognition accuracy was used as measure of performance. Different kinds of outdoor and indoor noise were used for studying. It is shown the superiority of training on noised speech methods over the competitive technique of training on clear speech. It has been found that training by means of noised speech allows reach high, abut 95…97%, recognition accuracy for about 5…10 dB signal-to-noise ratio. At the same time, training by means of clean speech allows reach the same accuracy for about 20…25 dB.
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