Amazigh Isolated-Word speech recognition system using Hidden Markov Model toolkit (HTK)
Amazigh Isolated-Word speech recognition system using Hidden Markov Model toolkit (HTK)
复制标题
使用隐马尔可夫模型工具包 (HTK) 的 Amazigh 孤立词语音识别系统
DOI：
10.1109/it4od.2016.7479305
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Mohamed Bellouki
中科院分区：
文献类型：
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作者：
Safaa Elouahabi;M. Atounti;Mohamed Bellouki
本文旨在构建一个独立于说话者的自动 Amazigh 孤立词语音识别系统。使用隐马尔可夫模型的隐马尔可夫模型工具包（HTK）已用于开发该系统。识别词汇由阿马齐格字母和数字组成。该系统经过训练，可以识别 Amazigh 的前 10 个数字和 33 个字母。梅尔频谱系数（MFCC）已用于提取特征。训练数据收集自 60 名演讲者，包括男性和女性。用于评估系统性能的测试数据是从 20 个扬声器收集的。实验结果表明，该系统的整体单词准确率达到80%。与训练数据库的大小相比，获得的初步结果非常令人满意，这鼓励我们提高系统性能以获得更高的识别率。
This paper aims to build a speaker-independent automatic Amazigh Isolated-Word speech recognition system. Hidden Markov Model toolkit (HTK) that uses hidden Markov Models has been used to develop the system. The recognition vocabulary consists on the Amazigh Letters and Digits. The system has been trained to recognize the Amazigh 10 first digits and 33 alphabets. Mel frequency spectral coefficients (MFCCs) have been used to extract the feature. The training data has been collected from 60 speakers including both males and females. The test-data used for evaluating the system-performance has been collected from 20 speakers. The experimental results show that the presented system provides the overall word-accuracy 80%. The initial results obtained are very satisfactory in comparison with the training database's size, this encourages us to increase system performance to achieve a higher recognition rate.