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Thai speech recognition using Double filter banks for basic voice commanding

机译:使用双重过滤器库进行基本语音命令的泰语语音识别

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This paper describes the methodology to recognize Thai speech words by integrating two approaches e.g., Double filter banks and Euclidian distance in a feature extraction and the recognition processes, respectively. Firstly, the speech signals are transformed into the 3-dimension of signal or spectrogram. The spectrogram displays energy information along both time and frequency axes. Secondly, the frequencies to be within the bin spread and correlated them with each triangular filter. Thus, each bin holds a weighted sum, and represents the spectral magnitude in that filter bank channel. Finally, the filter banks are normalized into the normalized bank for comparison between the entry signal of word and various words of dictionary. The Euclidian distance is used to measure the similarity between them. The system was evaluated for its accuracy and stability in performing various conditions. The accuracy was tested with 9,000 speeches from several volunteers. The average accuracy rate is about 96.3 %. The results show that the evaluation was beyond satisfaction for every aspect.
机译:本文介绍了通过在特征提取和识别过程中分别集成双重过滤库和欧氏距离这两种方法来识别泰语语音的方法。首先,语音信号被转换成信号或频谱图的三维。频谱图沿时间和频率轴显示能量信息。其次,频率在频点内,并且将其与每个三角形滤波器相关联。因此,每个单元保持一个加权和,并表示该滤波器组通道中的频谱幅度。最后,将滤波器组归一化为归一化组,以比较单词的输入信号和字典中的各个单词。欧几里得距离用于测量它们之间的相似性。对系统在各种条件下的准确性和稳定性进行了评估。通过几位志愿者的9,000场演讲对准确性进行了测试。平均准确率约为96.3%。结果表明,该评估在各个方面都超出了人们的满意程度。

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