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General Steganalysis Method of Compressed Speech Under Different Standards
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作者 Peng Liu Songbin Li +2 位作者 Qiandong Yan Jingang Wang Cheng Zhang 《Computers, Materials & Continua》 SCIE EI 2021年第8期1565-1574,共10页
Analysis-by-synthesis linear predictive coding(AbS-LPC)is widely used in a variety of low-bit-rate speech codecs.Most of the current steganalysis methods for AbS-LPC low-bit-rate compressed speech steganography are sp... Analysis-by-synthesis linear predictive coding(AbS-LPC)is widely used in a variety of low-bit-rate speech codecs.Most of the current steganalysis methods for AbS-LPC low-bit-rate compressed speech steganography are specifically designed for a specific coding standard or category of steganography methods,and thus lack generalization capability.In this paper,a general steganalysis method for detecting steganographies in low-bit-rate compressed speech under different standards is proposed.First,the code-element matrices corresponding to different coding standards are concatenated to obtain a synthetic code-element matrix,which will be mapped into an intermediate feature representation by utilizing the pre-trained dictionaries.Then,bidirectional long short-term memory is employed to capture long-term contextual correlations.Finally,a code-element affinity attention mechanism is used to capture the global inter-frame context,and a full connection structure is used to generate the prediction result.Experimental results show that the proposed method is effective and better than the comparison methods for detecting steganographies in cross-standard low-bit-rate compressed speech. 展开更多
关键词 Cross-standard compressed speech STEGANALYSIS ATTENTION
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High Performance Speech Compression System 被引量:6
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作者 Ke Liu, Zhichun Mu, Zhong Wang Information Engineering School, University of Science & Technology Beijing, Beijing 100083, China 《Journal of University of Science and Technology Beijing》 CSCD 2001年第3期229-233,共5页
Since Pulse Code Modulation emerged in 1937, digitized speech has experienced rapid development due to its outstanding voice quality, reliability, robustness and security in communication. But how to reduce channel wi... Since Pulse Code Modulation emerged in 1937, digitized speech has experienced rapid development due to its outstanding voice quality, reliability, robustness and security in communication. But how to reduce channel width without loss of speech quality remains a crucial problem in speech coding theory. A new full-duplex digital speech communication system based on the Vocoder of AMBE-1000(TM) and microcontroller ATMEL 89C51 is introduced. It shows higher voice quality than current mobile phone system with only a quarter of channel width needed for the latter. The prospective areas in which the system can be applied include satellite communication, IP Phone, virtual meeting and the most important, defence industry. 展开更多
关键词 digital signal processing digital speech compression digital communication full-duplex coding rate
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Speech compression scheme based on wavelet transform and vector quantization
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作者 LI Shuhong SANG Enfang(Dept. of Underwater, Acoustic, Harbin Engineering University Harbin 150001) 《Chinese Journal of Acoustics》 1999年第4期344-352,共9页
A coding method of speech compression, which is based on Wavlet Transform and Vector Quantization (VQ), is developed and studied. The Wavlet Thansform or Wavlet Packet Thansform is used to process the speech signal, t... A coding method of speech compression, which is based on Wavlet Transform and Vector Quantization (VQ), is developed and studied. The Wavlet Thansform or Wavlet Packet Thansform is used to process the speech signal, then VQ is used to compress the coefficients of Wavlet Thansform, and the entropy coding is used to decrease the bit rate. The experimental results show that the speech signal, sampled by 8 kHz sampling rate and 8 bit quatisation,i.e., 64 kbit/s bit rate, can be compressed to 6 - 8 kbit/s, and still have high speech quality,and the low-delay, only 8 ms. 展开更多
关键词 IEEE In speech compression scheme based on wavelet transform and vector quantization
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