Joint source-channel MMSE-decoding of speech parameters

S. Heinen, P. Vary
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引用次数: 2

Abstract

For speech transmission in digital land mobile telephony, effective compression algorithms have to be used to achieve a high bandwidth efficiency. Furthermore, a variety of adverse transmission effects make it necessary to employ powerful error control techniques to keep bit error rates tolerably low and thus to guarantee a high speech duality. Speech compression is designed to remove irrelevancy and redundancy from the speech signal. Yet measuring the statistical properties of speech parameters extracted by practical compression schemes shows that a considerable amount of redundancy still remains, either in terms of non-uniform distribution or due to time-correlation of parameters extracted from subsequent speech segments. In this contribution, we propose a new minimum mean square error (MMSE) decoder for block-oriented trellis codes, that is able to exploit the time-correlation of subsequent parameter sets. The decoder yields non-discrete speech parameter mean square (MS) estimates. Thus it combines two approaches to exploit residual redundancy: source controlled channel decoding (SCCD) (Hagenauer 1995) and soft bit source decoding (SBSD) (Fingscheidt and Vary 1997) in one algorithm.
联合源信道mmse解码语音参数
数字陆地移动电话的语音传输必须采用有效的压缩算法,以达到较高的带宽效率。此外,各种不利的传输影响使得有必要采用强大的错误控制技术来保持误码率可容忍的低,从而保证高语音对偶性。语音压缩的目的是去除语音信号中的不相关和冗余。然而,测量实际压缩方案提取的语音参数的统计特性表明,由于从后续语音段提取的参数的不均匀分布或时间相关性,仍然存在相当数量的冗余。在这篇贡献中,我们提出了一种新的最小均方误差(MMSE)解码器,用于面向块的网格码,它能够利用后续参数集的时间相关性。解码器产生非离散语音参数均方(MS)估计。因此,它结合了两种方法来利用剩余冗余:源控制信道解码(SCCD) (Hagenauer 1995)和软位源解码(SBSD) (Fingscheidt和Vary 1997)在一个算法中。
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