An MFCC-Based Speaker Identification System
An MFCC-Based Speaker Identification System
复制标题
基于MFCC的说话人识别系统
DOI：
10.1109/aina.2017.130
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Guan
中科院分区：
文献类型：
--
作者：
Fang;Guan
如今，许多语音识别应用已经被世界各地的人们所使用。典型的例子有iPhone的SIRI、谷歌语音识别系统、语音操作的手机等。相反，现阶段的说话人识别还相对不成熟。因此，在本文中，我们研究了一种说话人识别技术，该技术首先取一个人的原始语音信号，例如Bob，然后对信号的音频能量进行归一化。然后利用傅里叶变换方法将音频信号从时域转换到频域。接下来，利用基于mfcc的人类听觉滤波模型识别不同频率的能量水平作为Bob声音的量化特征。进一步，利用高斯混合模型的概率密度函数来表示量化特征的分布，作为Bob的特定声学模型。当接收到一个未知的人，例如x的声音时，系统以相同的程序处理该声音，并将处理结果（即x的声学模型）与事先在声学模型数据库中收集的已知人的声学模型进行比较，以确定谁是最有可能的说话者。
Nowadays, many speech recognition applications have been used by people in the world. Typical examples are the SIRI of iPhone, Google speech recognition system, and mobile phones operated by voice, etc. On the contrary, speaker identification in its current stage is relatively immature. Therefore, in this paper, we study a speaker identification technique which first takes the original voice signals of a person, e.g., Bob, and then normalizes the audio energies of the signals. After that, the audio signals is converted from time domain to frequency domain by employing Fourier transformation approach. Next, a MFCC-based human auditory filtering model is utilized to identify the energy levels of different frequencies as the quantified characteristics of Bob's voice. Further, the probability density function of Gaussian mixture model is utilized to indicate the distribution of the quantified characteristics as Bob's specific acoustic model. When receiving an unknown person, e.g., x's voice, the system processes the voice with the same procedure, and compares the processing result, which is x's acoustic model, with known-people's acoustic models collected in an acoustic-model database beforehand to identify who the most possible speaker is.
DOI：
10.1109/89.365379
发表时间：
1995-01-01
期刊：
IEEE TRANSACTIONS ON SPEECH AND AUDIO PROCESSING
影响因子：
--
作者：
REYNOLDS, DA;ROSE, RC
通讯作者：
ROSE, RC