计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2015年
9期
207-212
,共6页
共振峰%经验模态分解%固有模态函数%加权Mel倒谱%离散余弦变换
共振峰%經驗模態分解%固有模態函數%加權Mel倒譜%離散餘絃變換
공진봉%경험모태분해%고유모태함수%가권Mel도보%리산여현변환
formant%Empirical Mode Decomposition(EMD)%Intrinsic Mode Functions(IMF)%Weighted Mel-Cepstrum coefficient(WMCEP)%Discrete Cosine Transform(DCT)
提出了一种利用经验模态分解（Empirical Mode Decomposition，EMD）和加权Mel倒谱（Weighted Mel-Cepstrum coefficients，WMCEP）提取语音信号共振峰的算法。对语音信号进行EMD分解，找出含有共振峰的固有模态函数（Intrinsic Mode Function，IMF），并将其重构得到一个新的重构语音信号。对重构语音信号进行加权Mel倒谱分析，获得包含频谱主要成分的加权Mel倒谱系数；利用离散余弦平滑算法，从加权Mel倒谱系数获得谱包络，并从谱包络的峰值位置获得候选共振峰；根据共振峰的连续性约束条件和频率范围，从候选共振峰筛选得到共振峰的估计值。实验结果表明，该算法比单独使用WMCEP提取的共振峰误差更小，而且在信噪比小于20 dB时仍然能够准确提取出共振峰。
提齣瞭一種利用經驗模態分解（Empirical Mode Decomposition，EMD）和加權Mel倒譜（Weighted Mel-Cepstrum coefficients，WMCEP）提取語音信號共振峰的算法。對語音信號進行EMD分解，找齣含有共振峰的固有模態函數（Intrinsic Mode Function，IMF），併將其重構得到一箇新的重構語音信號。對重構語音信號進行加權Mel倒譜分析，穫得包含頻譜主要成分的加權Mel倒譜繫數；利用離散餘絃平滑算法，從加權Mel倒譜繫數穫得譜包絡，併從譜包絡的峰值位置穫得候選共振峰；根據共振峰的連續性約束條件和頻率範圍，從候選共振峰篩選得到共振峰的估計值。實驗結果錶明，該算法比單獨使用WMCEP提取的共振峰誤差更小，而且在信譟比小于20 dB時仍然能夠準確提取齣共振峰。
제출료일충이용경험모태분해（Empirical Mode Decomposition，EMD）화가권Mel도보（Weighted Mel-Cepstrum coefficients，WMCEP）제취어음신호공진봉적산법。대어음신호진행EMD분해，조출함유공진봉적고유모태함수（Intrinsic Mode Function，IMF），병장기중구득도일개신적중구어음신호。대중구어음신호진행가권Mel도보분석，획득포함빈보주요성분적가권Mel도보계수；이용리산여현평활산법，종가권Mel도보계수획득보포락，병종보포락적봉치위치획득후선공진봉；근거공진봉적련속성약속조건화빈솔범위，종후선공진봉사선득도공진봉적고계치。실험결과표명，해산법비단독사용WMCEP제취적공진봉오차경소，이차재신조비소우20 dB시잉연능구준학제취출공진봉。
This paper presents a method to realize formants extraction from speech signal. The speech signal is decom-posed with Empirical Mode Decomposition(EMD)to obtain a set of formant-specific Intrinsic Mode Functions(IMF). The new speech signal is then generated by adding the IMFs. The Weighted Mel-Cepstrum Coefficients(WMCC), which contain main components of spectrum, are calculated from the new speech signal by using weighted mel-cepstrum analysis. The Discrete Cosine Transform(DCT)based smooth algorithm is then applied to the WMCCs to obtain the smooth con-tour of spectrum in which the peaks of contour are candidate formants. The formant frequencies are selected from candidate formants according to the continuity constrain and the frequency range of formants. Tests show that the errors of this method outperform the weighted mel-cepstrum based method. When signal-to-noise ratio is less than 20 dB, the proposed method still can accurately extract the formants.
