说话者识别技术作为一个新一代的门禁安防技术也已经出现商业应用。
Speaker identification technology has appeared in industrial applications as a next generation security technology.
一直以来，音频信号的处理主要集中于语音识别、说话者识别等语音处理方面的研究。
Always, the processing of the audio frequency signal is mainly concentrated on speech processing, such as speech recognition and talks identify etc.
在Web会议页面中创建一个附加小部件以帮助团队新成员自动识别说话者。
Create an additional widget on your Web-conferencing page to help automatically identify speakers to new members of your team.
Sphinx特别是Sphinx - 4包提供了所有必需选项，可以在与说话者不相关的环境中可靠识别非常小(但仍然有用)的词汇表。
Sphinx and specifically the Sphinx-4 package delivers all the options we need to reliably recognize a very small (yet useful) vocabulary in a speaker-independent context.
正如可以在演示视频中看到的那样，结果并不是100%精确，但是却可以有效地识别说话者。
As you can see from the demonstration video, the results are not 100-percent accurate, but do provide for a useful augmentation of identifiable speakers.
要实现与说话者不相关的大型词汇表识别，语言识别技术还要2到10年的路要走。
Speech recognition is a technology that always seems two to 10 years away from speaker-independent recognition of a large vocabulary.
研究者所采用的功能磁共振方法，能够以百分之百地准确率识别正常人回答这类问题时的大脑活动，但是在不能移动或是不能说话的人中，还没有试用过这种方法。
The fMRI method used can decipher the brain's answers to questions in healthy people with 100 percent accuracy, but it has never been tried before in patients unable to move or speak.
为了更好地将区分式分类方法应用于说话者确认系统中，构建序列核支持向量机已成为说话人识别领域的研究热点与趋势。
To apply the discriminative classifier in the speaker recognition, the building sequence kernel support vector machine(SVM) becomes the trend in the field.
声纹识别是语音识别的一种，它根据测试语音来辨别说话者的身份。
Voiceprint Recognition(VPR) is one of Biometric technologies which can know who are you by your words.
因此，研究一种识别率高、鲁棒性强的说话人识别方法是国内外众多研究者努力的目标。
Therefore, a more robust method for speaker recognition with high accuracy of recognition rate is the aim for researchers at home and abroad.
更早以前的研究也得出过相似的结果：比如过去有研究表明，孤独的人更善于准确识别面部表情，解读说话者语气中蕴含的信息。
Previous research echoes these new results: Past studies have suggested, for example, that the lonelier people are better at accurately reading facial expressions and decoding tone of voice.
与语音识别不同的是，说话人识别系统力求选取那些话者间差异大而话者本身的差异小的参数或参数组合。
Different from Speech Recognition, Speaker Recognition systems choose the parameter or parameters which had great difference between speakers and little difference about itself.
正因为说话人识别具有如此广阔的应用前景，近年来在生物认证技术领域中越来越受到研究者的关注。
Because of that, it is pay attention to by the researcher more and more in the biometrics techniques realm in recent years.
分别利用语音的短时和长时特征识别说话者的五种情感状态，即生气、高兴、悲伤、惊奇和一种无情感状态。
Two kinds of speech features, long-term and short-term features are studied, to classify five emotional states: anger, happiness, sadness, surprise and a neutral state.
分别利用语音的短时和长时特征识别说话者的五种情感状态，即生气、高兴、悲伤、惊奇和一种无情感状态。
Two kinds of speech features, long-term and short-term features are studied, to classify five emotional states: anger, happiness, sadness, surprise and a neutral state.
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