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Feature extraction

Feature extraction. 在理論上求取 MFCC 的流程. 語音訊號. 取 30ms 為一個音框. frame. frame. H(n)-H0.95H(n). Pre-emphasis. 抑制 sidelobe 部分的信號，把 peak 凸顯出來. Hamming. 轉成頻率 domain 較易分析. FFT. 求振幅. || ||. Filter Bank (Triangle). Mel (f)=2595 log (1+f/700). 10. log. Inverse Cosine Transform. 求梅爾參數.

chiquita-warren
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Feature extraction

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  1. Feature extraction

  2. 在理論上求取MFCC的流程 語音訊號 取30ms為一個音框 frame frame H(n)-H0.95H(n) Pre-emphasis 抑制sidelobe部分的信號，把peak凸顯出來 Hamming 轉成頻率domain較易分析 FFT 求振幅 || || Filter Bank (Triangle) Mel (f)=2595 log (1+f/700) 10 log Inverse Cosine Transform 求梅爾參數 features

  3. begin • Initial MFCC • hamming table • FFT table • triangular filter bank coefficients filter • find Low, upper freq and space • find center freq • set response for every filter • all channels • set upper and lowerside spk eof 1 0 • Open file • fea • len • dc bias utt utt>Nutter 1 0 • open vat file • utterance count ++ • Read head of vat file • read 256 byte header • get sample number If status = 1 ? (check condition and transcription of waveform) no yes • compute total frame Extract MFCC • save feature out to • file • close fea , len • file end

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