The speaker recognition system based on vector quantization method is introduced by this text.
介绍了基于改进矢量量化(VQ)方法的说话人识别系统。
参考来源 - 基于改进VQ算法的说话人识别According to its application, speaker recognition can be classified as speaker identification and speaker verification.
从应用场合的角度,说话者识别可分为说话者辨认和说话者确认。
参考来源 - 基于时间序列分析方法的说话者识别Speaker identification was a biometrics that identify people via their voice, and VQ was the best model in the of speaker recognition because the method has a ability of condensing a lot of data.
语者鉴定是根据人的声音来鉴定人的一种生物认证技术,有十分广阔的应用前景。 矢量量化模型有着可将大量数据进行压缩的特点,因此,在语者识别领域中有很好的应用前景。
参考来源 - 基于矢量量化算法的语者鉴定研究Experimental results show that using SVM-GMM model can improve the open-set speaker recognition rate effectively.
实验结果表明，使用SVM-GMM模型能有效地提高开集说话人识别的识别率。
参考来源 - 基于SVM·2,447,543篇论文数据，部分数据来源于NoteExpress
以上来源于: WordNet
Speaker recognition system source code integrity, and can be used directly.
说话人识别系统的源代码完整，并可以直接使用。
This shows that the neural network is a potential method for speaker recognition.
这说明神经网络对于说话人识别是一种很有潜力的方法。
SONAR both supports Automatic Speaker Recognition and Automatic Speech Recognition.
SONAR可同时支持说话人识别与语音识别。
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