基于凸集投影的语音频谱参数恢复

U. Visitkitjakarn, W. Chan, Yongyi Yang
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引用次数: 2

摘要

先前的研究表明,通过在频谱参数量化和/或解码过程中保持语音频谱的“动态”,可以提高编码语音的质量。我们探索使用凸集投影(POCS)技术从语音谱参数的量化版本中恢复语音谱参数。与先前的工作不同,POCS方法使我们能够获得满足精确约束的解。在我们的POCS恢复算法中使用了两个约束集:一组约束参数轨迹的“粗糙度”,另一组将参数限制在适当的量化划分单元中。我们的算法的模拟持续地在主观质量和客观失真测量方面产生改进。
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Recovery of speech spectral parameters using convex set projection
Previous works have demonstrated that by preserving speech spectral "dynamics" during spectral parameter quantization and/or decoding, the quality of coded speech can be improved. We explore the use of projections onto convex sets (POCS) techniques to recover speech spectral parameters from their quantized versions. Unlike prior works, the POCS approach enables us to obtain solutions that satisfy precise constraints. Two constraint sets are used in our POCS recovery algorithm: one set constrains the "roughness" of the parameter trajectories, and the other set confines the parameters to the proper quantizer partition cells. Simulation of our algorithm has consistently produced improvements in both the subjective quality and objective distortion measurements.
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