叠加特征信息辅助的语音传输与重构
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摘要
为改善压缩语音传输系统的重构精度且不增加系统的频谱开销,提出一种叠加特征信息辅助的语音压缩传输与重构方法。提出方法首先提取稀疏语音信号的特征信息;抽取的特征信息以叠加序列方式叠加在压缩语音信号上进行传输;接收机重构时,借助特征信息辅助重构算法进行语音重构。分析与仿真结果表明,相比于传统的压缩感知语音重构方法,在较高信噪比或较低压缩率情况下,提出方法可改善语音重构精度,且不增加传输系统的频谱开销。
To improve the reconstruction accuracy of compressed speech transmission system without increasing the spectrum resource overhead, a method of speech compression transmission and reconstruction assisted by superimposed feature information is proposed in this paper. The feature information is extracted from the sparse speech signal. The extracted feature information is superimposed on the compressed speech signal for transmission. At the receiver, the superimposed feature information is recovered, which is employed to assist the reconstruction algorithm to reconstruct the speech signal. Compared with the traditional compressed sensing-based speech reconstruction method at higher signal-tonoise ratio or lower compression ratio, the analysis and simulation results show that the proposed method can improve the speech reconstruction accuracy without increasing the spectrum resource overhead of the transmission system.
To improve the reconstruction accuracy of compressed speech transmission system without increasing the spectrum resource overhead, a method of speech compression transmission and reconstruction assisted by superimposed feature information is proposed in this paper. The feature information is extracted from the sparse speech signal. The extracted feature information is superimposed on the compressed speech signal for transmission. At the receiver, the superimposed feature information is recovered, which is employed to assist the reconstruction algorithm to reconstruct the speech signal. Compared with the traditional compressed sensing-based speech reconstruction method at higher signal-tonoise ratio or lower compression ratio, the analysis and simulation results show that the proposed method can improve the speech reconstruction accuracy without increasing the spectrum resource overhead of the transmission system.
引文
[1] Zhilyakov E G,Belov S P,Belove A S,et al.About speech data compression[J].Journal of Fundamental and Applied Sciences,2017,9:1301-1312.
[2] Shokri S,Ismail M,Zainal N,et al.Audio-speech watermarking using a channel equalizer[J].Wireless Personal Communications,2017,95(4):4457-4476.
[3] Liu W,Hu A.A subband excitation substitute based scheme for narrowband speech watermarking[J].Frontiers Information Technology Electronic Engineering,2017,18(5):627-643.
[4] Zhang Q Y,Yang Z P,Huang Y B,et al.Robust speech perceptual hashing algorithm based on linear predication residual of G.729 speech codec[J].International Journal of Innovative Computing,Information and Control,2015,11(6):2159-2175.
[5]童新,卿朝进,张岷涛,等.基于模式化压缩感知的帧定时同步研究[J].计算机工程与应用,2017,53(13):119-124.
[6]王维,卿朝进,万东琴,等.单比特压缩感知帧定时同步[J].计算机工程与应用,2018,54(15):57-61.
[7] Qing Chaojin,Dong Xiucheng,Hong Peng,et al.Frame synchronization based on compressed sensing with correlation rule[J].International Journal of Information and Communication Technology,2016,9(3):271-281.
[8] Baraniuk R G.Compressive sensing[J].IEEE Signal Processing Magazine,2007,24(4):118-121.
[9] Giacobello D,Christensen M G,Murthi M N,et al.Sparse linear prediction and its applications to speech processing[J].IEEE Transactions on Audio,Speech,and Language Processing,2012,20(5):1644-1657.
[10] Shawky H,Abd-Elnaby M,Rihan M,et al.Efficient compression and reconstruction of speech signals using compressed sensing[J].International Journal of Speech Technology,2017,20(4):851-857.
[11] Stankovi?L,Brajovi?M.Analysis of the reconstruction of sparse signals in the DCT domain applied to audio signals[J].IEEE/ACM Transactions on Audio,Speech,and Language Processing,2018,26(7):1220-1235.
[12] Parthasarathy G,Abhilash G.Transform learning algorithm based on the probability of representation of signals[C]//European Signal Processing Conference,Kos,2017:1329-1333.
[13] Wang J C,Lee Y S,Lin C H,et al.Compressive sensingbased speech enhancement[J].IEEE/ACM Transactions on Audio,Speech,and Language Processing,2016,24(11):2122-2131.
[14] Bala S,Arif M.Effect of sparsity on speech compressed sensing[C]//2015 International Conference on Signal Processing,Computing and Control,Waknaghat,India,Sept2015:81-86.
[15] Qian Y,Chen W.Adaptive Bayesian compressed sensing based on speech frame signal[C]//2017 IEEE 9th International Conference on Communication Software and Networks,Guangzhou,2017:1047-1051.
[16] Enliang W,Yehui C,Defeng T.Speech signal processing and simulation analysis based on compressed sensing[C]//2016 Eighth International Conference on Measuring Technology and Mechatronics Automation,Macau,2016:617-620.
[17] Derouaz W,Merazi-Meksen T.Speech compressive sensing with?1-minimzation and iteratively reweighted least squares-?p-minimization:a comparative study[C]//20175th International Conference on Electrical EngineeringBoumerdes(ICEE-B),Boumerdes,2017:1-4.
[18] Xue H,Sun L,Ou G.Speech reconstruction based on compressed sensing theory using smoothed L0 algorithm[C]//2016 8th International Conference on Wireless Communications&Signal Processing(WCSP),Yangzhou,2016:1-4.
[19] Wu D,Zhu W P,Swamy M N S.The theory of compressive sensing matching pursuit considering time-domain noise with application to speech enhancement[J].IEEE/ACM Transactions on Audio,Speech,and Language Processing,2014,22(3):682-696.
[20]张殿飞,杨震,胡海峰.含噪语音压缩感知自适应快速重构算法[J].信号处理,2016,32(9):1065-1071.
[21] Yang H,Hao D,Sun H,et al.Speech enhancement using orthogonal matching pursuit algorithm[C]//International Conference on Orange Technologies,Xi’an,2014:101-104.
[22]刘秋格,穆晓敏,陆彦辉.叠加Chirp训练序列的OFDM信道估计[J].计算机工程与应用,2011,47(31):97-100.
[23] Tahir Y H,Al-Hussaibi W,Ng C K,et al.Unequal error protection for wireless data transmission using superposition coding with feedback[C]//International Conference on Innovations in Information Technology,Al Ain,2008:426-429.
[24] Xu D,Huang Y,Yang L.Feedback of Downlink Channel state information based on superimposed coding[J].IEEE Communications Letters,2007,11(3):240-242.
[25] Yu S,Wang R,Wan W,et al.Compressed sensing in audio signals and it’s reconstruction algorithm[C]//International Conference on Audio,Language and Image Processing,Shanghai,2012:947-952.
[26] Tropp J A,Gilbert A C.Signal recovery from random measurements via orthogonal matching pursuit[J].IEEE Transactions on Information Theory,2007:4655-4666.
[27]王永琦,杨洋.基于听觉特性的DCT域数字音频水印算法[J].计算机工程与应用,2008,44(3):88-90.
[28] Panda A,Srikanthan T.Psychoacoustic model compensation for robust speaker verification in environmental noise[J].IEEE Transactions on Audio,Speech,and Language Processing,2012,20(3):945-953.
[29]郭海燕,王天荆,杨震.DCT域的语音信号自适应压缩感知[J].仪器仪表学报,2010,31(6):1262-1268.
[30] Goyal V,Fletcher A,Rangan S.Compressive sampling and lossy compression[J].IEEE Signal Processing Maganize,2008,25(2):48-52.
[2] Shokri S,Ismail M,Zainal N,et al.Audio-speech watermarking using a channel equalizer[J].Wireless Personal Communications,2017,95(4):4457-4476.
[3] Liu W,Hu A.A subband excitation substitute based scheme for narrowband speech watermarking[J].Frontiers Information Technology Electronic Engineering,2017,18(5):627-643.
[4] Zhang Q Y,Yang Z P,Huang Y B,et al.Robust speech perceptual hashing algorithm based on linear predication residual of G.729 speech codec[J].International Journal of Innovative Computing,Information and Control,2015,11(6):2159-2175.
[5]童新,卿朝进,张岷涛,等.基于模式化压缩感知的帧定时同步研究[J].计算机工程与应用,2017,53(13):119-124.
[6]王维,卿朝进,万东琴,等.单比特压缩感知帧定时同步[J].计算机工程与应用,2018,54(15):57-61.
[7] Qing Chaojin,Dong Xiucheng,Hong Peng,et al.Frame synchronization based on compressed sensing with correlation rule[J].International Journal of Information and Communication Technology,2016,9(3):271-281.
[8] Baraniuk R G.Compressive sensing[J].IEEE Signal Processing Magazine,2007,24(4):118-121.
[9] Giacobello D,Christensen M G,Murthi M N,et al.Sparse linear prediction and its applications to speech processing[J].IEEE Transactions on Audio,Speech,and Language Processing,2012,20(5):1644-1657.
[10] Shawky H,Abd-Elnaby M,Rihan M,et al.Efficient compression and reconstruction of speech signals using compressed sensing[J].International Journal of Speech Technology,2017,20(4):851-857.
[11] Stankovi?L,Brajovi?M.Analysis of the reconstruction of sparse signals in the DCT domain applied to audio signals[J].IEEE/ACM Transactions on Audio,Speech,and Language Processing,2018,26(7):1220-1235.
[12] Parthasarathy G,Abhilash G.Transform learning algorithm based on the probability of representation of signals[C]//European Signal Processing Conference,Kos,2017:1329-1333.
[13] Wang J C,Lee Y S,Lin C H,et al.Compressive sensingbased speech enhancement[J].IEEE/ACM Transactions on Audio,Speech,and Language Processing,2016,24(11):2122-2131.
[14] Bala S,Arif M.Effect of sparsity on speech compressed sensing[C]//2015 International Conference on Signal Processing,Computing and Control,Waknaghat,India,Sept2015:81-86.
[15] Qian Y,Chen W.Adaptive Bayesian compressed sensing based on speech frame signal[C]//2017 IEEE 9th International Conference on Communication Software and Networks,Guangzhou,2017:1047-1051.
[16] Enliang W,Yehui C,Defeng T.Speech signal processing and simulation analysis based on compressed sensing[C]//2016 Eighth International Conference on Measuring Technology and Mechatronics Automation,Macau,2016:617-620.
[17] Derouaz W,Merazi-Meksen T.Speech compressive sensing with?1-minimzation and iteratively reweighted least squares-?p-minimization:a comparative study[C]//20175th International Conference on Electrical EngineeringBoumerdes(ICEE-B),Boumerdes,2017:1-4.
[18] Xue H,Sun L,Ou G.Speech reconstruction based on compressed sensing theory using smoothed L0 algorithm[C]//2016 8th International Conference on Wireless Communications&Signal Processing(WCSP),Yangzhou,2016:1-4.
[19] Wu D,Zhu W P,Swamy M N S.The theory of compressive sensing matching pursuit considering time-domain noise with application to speech enhancement[J].IEEE/ACM Transactions on Audio,Speech,and Language Processing,2014,22(3):682-696.
[20]张殿飞,杨震,胡海峰.含噪语音压缩感知自适应快速重构算法[J].信号处理,2016,32(9):1065-1071.
[21] Yang H,Hao D,Sun H,et al.Speech enhancement using orthogonal matching pursuit algorithm[C]//International Conference on Orange Technologies,Xi’an,2014:101-104.
[22]刘秋格,穆晓敏,陆彦辉.叠加Chirp训练序列的OFDM信道估计[J].计算机工程与应用,2011,47(31):97-100.
[23] Tahir Y H,Al-Hussaibi W,Ng C K,et al.Unequal error protection for wireless data transmission using superposition coding with feedback[C]//International Conference on Innovations in Information Technology,Al Ain,2008:426-429.
[24] Xu D,Huang Y,Yang L.Feedback of Downlink Channel state information based on superimposed coding[J].IEEE Communications Letters,2007,11(3):240-242.
[25] Yu S,Wang R,Wan W,et al.Compressed sensing in audio signals and it’s reconstruction algorithm[C]//International Conference on Audio,Language and Image Processing,Shanghai,2012:947-952.
[26] Tropp J A,Gilbert A C.Signal recovery from random measurements via orthogonal matching pursuit[J].IEEE Transactions on Information Theory,2007:4655-4666.
[27]王永琦,杨洋.基于听觉特性的DCT域数字音频水印算法[J].计算机工程与应用,2008,44(3):88-90.
[28] Panda A,Srikanthan T.Psychoacoustic model compensation for robust speaker verification in environmental noise[J].IEEE Transactions on Audio,Speech,and Language Processing,2012,20(3):945-953.
[29]郭海燕,王天荆,杨震.DCT域的语音信号自适应压缩感知[J].仪器仪表学报,2010,31(6):1262-1268.
[30] Goyal V,Fletcher A,Rangan S.Compressive sampling and lossy compression[J].IEEE Signal Processing Maganize,2008,25(2):48-52.