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Isolated Chinese lyrics with accompaniment recognition based on SVM

机译:基于SVM的伴随着识别的孤立的中国歌词

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The speech recognition technology is one of the hot spots in the field of audio technology. For the recognition of the lyrics with the accompaniment, there are two commonly used methods, one is applying automatic speech recognition technology to singing recognition, the other way is using sound classification, extracting audio features, and then using pattern matching classifier for classification. In this paper, we use sound classification method, adopt self-built experimental database where 31 classes Chinese isolated lyrics (Total 4650) are intercepted from different songs. And then use these words as the units. Considering speaking and singing sharing similar mechanism, we extract 39-dimensional MFCC feature parameters which are widely used in speech recognition. Combined with training materials, adjust kernel parameters and choose functions to train SVM classifier. After that, the trained SVM classification system is used to recognize the lyrics, and the average recognition accuracy rate is 42.80%.
机译:语音识别技术是音频技术领域的热点之一。为了使伴随着伴奏的歌词,有两个常用的方法,一个是将自动语音识别技术应用于唱歌识别,另一种方式是使用声音分类,提取音频功能,然后使用模式匹配分类器进行分类。在本文中,我们使用Sound Classification方法,采用自建实验数据库,其中31个中国孤立的歌词(总共4650)截取了不同的歌曲。然后使用这些单词作为单位。考虑说话和唱歌共享类似机制,我们提取39维MFCC特征参数,这些特征参数广泛用于语音识别。结合培训材料,调整内核参数,然后选择要训练SVM分类器的功能。之后,训练有素的SVM分类系统用于识别歌词,平均识别精度率为42.80%。

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