一种用来组成说话人验证系统的软件包
speaker-verification-toolkit的Python项目详细描述
说话人验证工具包
本模块包含一些工具，用于进行简单的说话人验证。在
您可以使用PyPI下载它：
$pipinstallspeaker-verification-toolkit
要在自己的项目中导入和使用：
^{pr2}$使用
find_nearest_voice_data(voice_data_list,voice_sample)
根据此语音样本查找最近的语音数据。可以用来做出天真的接受/拒绝决定。在
voice_data_list: a list containing all voices data from the dataset.
voice_sample: the voice sample reference.
returns: the index of the element from voice_data_list that represents the nearest voice data.
compute_distance(sample1,sample3)
使用O（n）DTW算法计算样本1和样本2之间的距离
sample1: the mfcc data extracted from the audio signal 1.
sample2: the mfcc data extracted from the audio signal 2.
returns: Float number representing the minimum distance between sample1 and sample2.
extract_mfcc(signal_data,samplerate=16000,winlen=0.025,winstep=0.01)
从音频信号计算MFCC特征
signal: the audio signal from which to compute features. Should be an N*1 array.
samplerate: the sample rate of the signal we are working with, in Hz.
winlen: the length of the analysis window in seconds. Default is 0.025s (25 milliseconds).
winstep: the step between successive windows in seconds. Default is 0.01s (10 milliseconds).
returns: A numpy array of size (NUMFRAMES by numcep) containing features. Each row holds 1 feature vector.
extract_mfcc_from_wav_file(path,samplerate=16000,winlen=0.025,winstep=0.01)
从wav文件计算MFCC功能
path: the wav file path to be open.
samplerate: the wanted sample rate, in Hz. Default is 16000. If you want no resampling fill this argument with None.
winlen: the length of the analysis window in seconds. Default is 0.025s (25 milliseconds).
winstep: the step between successive windows in seconds. Default is 0.01s (10 milliseconds).
returns: A numpy array of size (NUMFRAMES by numcep) containing features. Each row holds 1 feature vector.
rms_silence_filter(data,samplerate=16000,segment_length=None,threshold=0.001135)
切断信号音频数据的静音部分。无法处理受环境噪声影响的信号数据。 您可以考虑在使用此静音过滤器之前应用噪声过滤器，或者确保环境噪声足够小，可以被视为静音。在
data: the audio signal data
samplerate: if no segment_length is given, segment_length will be equals samplerate/100 (around 0.01 secs per segment).
segment_length: the number of frames per segment. I.e. for a sample rate SR, a segment length equals SR/100 will represent a chunk containing 0.01 seconds of audio.
threshold: the threshold value. Values less than or equal values will be cut off. The default value was defined at [1] (see the references).
returns: the param "data" without silence parts.
参考文献
[1]-Muhammad Asadullah&Shibli Nisar，“语音处理的静音消除和端点检测方法”，国立计算机与新兴科学大学，白沙瓦
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