資源簡介
語音中準確的情緒識別對于智能醫(yī)療、智能娛樂和其他智能服務(wù)等應用程序非常重要。由于漢語語言的復雜性,漢語語音的高精度動作識別具有挑戰(zhàn)性。本文探討了如何提高語音情感識別的準確性,包括語音信號特征提取和情感分類方法。從語音樣本中提取五種特征:梅爾頻率倒譜系數(shù)(mfcc)、音調(diào)、共振峰、短期過零率和短期能量

代碼片段和文件信息
function?[?CC?FBE?frames?]?=?mfcc(?speech?fs?Tw?Ts?alpha?window?R?M?N?L?)
%?MFCC?Mel?frequency?cepstral?coefficient?feature?extraction.
%
%???MFCC(SFSTWTSALPHAWINDOWRMNL)?returns?mel?frequency?
%???cepstral?coefficients?(MFCCs)?computed?from?speech?signal?given?
%???in?vector?S?and?sampled?at?FS?(Hz).?The?speech?signal?is?first?
%???preemphasised?using?a?first?order?FIR?filter?with?preemphasis?
%???coefficient?ALPHA.?The?preemphasised?speech?signal?is?subjected?
%???to?the?short-time?Fourier?transform?analysis?with?frame?durations?
%???of?TW?(ms)?frame?shifts?of?TS?(ms)?and?analysis?window?function?
%???given?as?a?function?handle?in?WINDOW.?This?is?followed?by?magnitude?
%???spectrum?computation?followed?by?filterbank?design?with?M?triangular?
%???filters?uniformly?spaced?on?the?mel?scale?between?lower?and?upper?
%???frequency?limits?given?in?R?(Hz).?The?filterbank?is?applied?to?
%???the?magnitude?spectrum?values?to?produce?filterbank?energies?(FBEs)?
%???(M?per?frame).?Log-compressed?FBEs?are?then?decorrelated?using?the?
%???discrete?cosine?transform?to?produce?cepstral?coefficients.?Final
%???step?applies?sinusoidal?lifter?to?produce?liftered?MFCCs?that?
%???closely?match?those?produced?by?HTK?[1].
%
%???[CCFBEframeS]=MFCC(...)?also?returns?FBEs?and?windowed?frames
%???with?feature?vectors?and?frames?as?columns.
%
%???This?framework?is?based?on?Dan?Ellis‘?rastamat?routines?[2].?The?
%???emphasis?is?placed?on?closely?matching?MFCCs?produced?by?HTK?[1]
%???(refer?to?p.337?of?[1]?for?HTK‘s?defaults)?with?simplicity?and?
%???compactness?as?main?considerations?but?at?a?cost?of?reduced?
%???flexibility.?This?routine?is?meant?to?be?easy?to?extend?and?as?
%???a?starting?point?for?work?with?cepstral?coefficients?in?MATLAB.
%???The?triangular?filterbank?equations?are?given?in?[3].
%
%???Inputs
%???????????S?is?the?input?speech?signal?(as?vector)
%
%???????????FS?is?the?sampling?frequency?(Hz)?
%
%???????????TW?is?the?analysis?frame?duration?(ms)?
%?
%???????????TS?is?the?analysis?frame?shift?(ms)
%
%???????????ALPHA?is?the?preemphasis?coefficient
%
%???????????WINDOW?is?a?analysis?window?function?handle
%?
%???????????R?is?the?frequency?range?(Hz)?for?filterbank?analysis
%
%???????????M?is?the?number?of?filterbank?channels
%
%???????????N?is?the?number?of?cepstral?coefficients?
%?????????????(including?the?0th?coefficient)
%
%???????????L?is?the?liftering?parameter
%
%???Outputs
%???????????CC?is?a?matrix?of?mel?frequency?cepstral?coefficients
%??????????????(MFCCs)?with?feature?vectors?as?columns
%
%???????????FBE?is?a?matrix?of?filterbank?energies
%???????????????with?feature?vectors?as?columns
%
%???????????frameS?is?a?matrix?of?windowed?frames
%??????????????????(one?frame?per?column)
%
%???Example
%???????????Tw?=?25;???????????%?analysis?frame?duration?(ms)
%???????????Ts?=?10;???????????%?analysis?frame?shift?(ms)
%???????????alpha?=?0.97;??????%?preemphasis?coefficient
%???????????R?=?[?300?3700?];??%?frequency?range?to?
?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????7190??2018-04-21?21:05??mfcc.m
?????文件????????4797??2018-04-21?21:19??trifbank.m
?????文件???????10707??2018-04-23?16:30??unti
?????文件????????9006??2018-04-23?16:30??unti
?????文件????????6993??2018-04-21?21:19??vec2fr
?????文件???????65587??2019-05-28?20:16??語音情感識別代碼matlab.rtf
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