基于改进线性预测基音频率的语音情感识别系统
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作者单位:

长江大学

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中图分类号:

TP391.9

基金项目:

国家自然科学基金(62173049)


Speech Emotion Recognition System Based on Improved Linear Prediction Pitch Frequency
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Affiliation:

Yangtze University

Fund Project:

National Natural Science Foundation of China (62173049)

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    摘要:

    针对目前常见的语音特征提取方法应用于真实环境中,所提取的语音特征包含有噪声干扰的问题,进而导致情感识别时出现的分类模糊化情况,为此提出一种新的语音特征提取方法,即线性预测基音频率特征提取方法。它主要是基于线性预测系数来构建模型,利用构建的模型消除声道响应信息以及抑制噪声干扰。由于此方法对于分类模糊化问题没有得到较好改善,利用模型相同的LPCMCC来对线性预测基音频率进行改进,并设计基于线性预测基音频率、其改进特征、LPCMCC与SVM的语音情感识别对比实验。对比实验表明,此改进特征提取方法应用在情感识别领域的平均精度最高为84%,比线性预测基音频率和LPCMCC要高出22%、14%。为了测试此改进特征在真实环境中的分类效果,在此改进特征的基础上设计了一种基于MATLAB GUI技术的语音情感识别系统。实验结果表明这种新的改进特征能有效改善情感识别时出现的分类模糊化情况,基于此改进特征的语音情感系统能广泛地识别出噪声干扰下的说话人情感。能广泛地识别出噪声干扰下的说话人情感。

    Abstract:

    In view of the current common speech feature extraction methods applied to the real environment, the extracted speech feature contains noise interference, which leads to the classification ambiguity in emotion recognition. Therefore, a new speech feature extraction method, namely linear prediction pitch frequency feature extraction method, is proposed. It is mainly based on linear prediction coefficient to construct a model, using the constructed model to eliminate the vocal tract response information and suppress noise interference. As this method does not achieve a better improvement for the classification ambiguity problem that occurs in emotion recognition, the LPCMCC with the same model is used to improve linear prediction pitch frequency and the comparative experiments on speech emotion recognition based on linear prediction pitch frequency, its improved features, LPCMCC and SVM are designed. The comparative experiments indicate that the average accuracy of this improved feature extraction method in the field of emotion recognition is up to 84%, which is 22% and 14% higher than that of linear pitch frequency prediction and LPCMCC, respectively. In order to test the classification effect of the improved feature in the real environment, a speech emotion recognition system based on MATLAB GUI technology is designed on the basis of the improved feature. Experimental results show that this new improved feature can effectively improve the classification ambiguity in emotion recognition, and the speech emotion system based on the improved feature can widely recognize the speaker's emotion in the presence of the noise interference.

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汪兰兰,蔡昌新. 基于改进线性预测基音频率的语音情感识别系统[J]. 科学技术与工程, , ():

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  • 收稿日期:2021-11-23
  • 最后修改日期:2022-03-31
  • 录用日期:2022-04-30
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