基于GMM的MFCC阿拉伯语口语数字识别

2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT) Pub Date : 2012-10-01 DOI:10.1109/STUDENT.2012.6408392

N. Hammami, M. Bedda, N. Farah

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引用次数: 11

摘要

高斯混合模型(GMM)是一种传统的语音识别方法，以其在语音建模方面的有效性和可扩展性而闻名。本文提出了基于GMM分类器的阿拉伯语口语数字自动识别和语音识别特征提取的主要方法——Delta-Delta Mel-倒谱系数(DDMFCC)。实验结果与所得到的参数吻合较好;他们实现了99.31%的正确数字识别数据集，与之前的阿拉伯语口语数字语音识别工作相比，这是非常令人满意的。

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Spoken Arabic Digits recognition using MFCC based on GMM

Gaussian mixture model (GMM) is a conventional method for speech recognition, known for its effectiveness and scalability in speech modeling. This paper presents automatic recognition of the Spoken Arabic Digits based on (GMM) classifier and the leading approach for speech recognition features extraction Delta-Delta Mel- frequency cepstral coefficients (DDMFCC). The experimental results give the best result with the obtained parameters; they achieve a 99.31% correct digit recognition dataset which is very satisfactory compared to previous work on spoken Arabic digits speech recognition.

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来源期刊

2012 IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT)

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