{"title":"Spectral quantization of cepstral coefficients","authors":"R. Hagen","doi":"10.1109/ICASSP.1994.389244","DOIUrl":null,"url":null,"abstract":"Studies the cepstral coefficients as a suitable representation of the linear prediction filter for spectral coding purposes. Spectral coding methods in predictive speech coders are usually evaluated using the spectral distance measure. The average spectral distance combined with a measure of the percentage of spectra with high distortion are used to predict the perceptual quality when quantizing the prediction filter. The authors show that the spectral distance is equivalent to a squared error in the cepstral domain. Methods for spectral quantization using vector quantization of cepstral coefficients are analyzed. Better results than for quantization of line spectrum frequencies are reported for both single-stage VQ at 11-14 bits as well as 2-stage VQ at 18-22 bits. It is concluded that the cepstral coefficients are the right representation for LPC spectral coding purposes.<<ETX>>","PeriodicalId":290798,"journal":{"name":"Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.1994.389244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

Abstract

Studies the cepstral coefficients as a suitable representation of the linear prediction filter for spectral coding purposes. Spectral coding methods in predictive speech coders are usually evaluated using the spectral distance measure. The average spectral distance combined with a measure of the percentage of spectra with high distortion are used to predict the perceptual quality when quantizing the prediction filter. The authors show that the spectral distance is equivalent to a squared error in the cepstral domain. Methods for spectral quantization using vector quantization of cepstral coefficients are analyzed. Better results than for quantization of line spectrum frequencies are reported for both single-stage VQ at 11-14 bits as well as 2-stage VQ at 18-22 bits. It is concluded that the cepstral coefficients are the right representation for LPC spectral coding purposes.<>
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倒谱系数的谱量化
研究了倒谱系数作为谱编码目的的线性预测滤波器的合适表示。预测语音编码器中的频谱编码方法通常使用频谱距离度量来评估。在量化预测滤波器时,使用平均光谱距离和高失真光谱百分比来预测感知质量。结果表明,谱距相当于倒谱域的平方误差。分析了利用倒谱系数矢量量化实现谱量化的方法。在11-14位的单级VQ和18-22位的两级VQ中,都报道了比线谱频率量化更好的结果。结果表明,倒谱系数是LPC频谱编码的正确表示形式。
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