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语音情绪分析
This project forked from willsongrui/signal_process
语音情绪分析
class Speech: 成员变量: nchannels: 声道数 sampleWidth: 采样数据带宽 sampleRate: 采样率 nframes: 总采样数据数目 rawData: 实际的采样数据 totalLength: 时间长度 speechSegment: 通话有声段 frame: 将rawData分帧后保存的list frameSize: 帧的长度 overLap: 帧重复段的长度 step: 每一帧的步长(frameSize - overLap) frameNum: 总帧数 zcr: 短时的过零率。计算方法中涉及一个zcrThread. volume: 每一帧的音量。计算方法是10*log((每一帧的音量/最大音量)^2) speed: isBlank: 是否为空白录音 absVolume: 音量的绝对值。计算方法是每一帧数据的绝对值和 shortTimeEnergy: 短时能量。 和音量的区别:音量除以最大音量,而短时能量不。 ezr: energy-zero-rate ezm: energy-zero-multiplication pitchSeg: 基频段。对于每一个speechSeg对应一个pitchSeg,每个pitchSeg保存着每一个元音的开始和结尾位置 成员函数: getSpeechSegmentByAbsVolume: 通过音量的绝对值找到通话有声段,计算方法是根据absVolume参数,通过双门限法(minLen,minSilence) 得到有声段的区域,保存在speechFrame成员变量中 energyZeroCount: 能量-过零率比。 getFramePitch:
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