Speech quality prediction for artificial bandwidth extension algorithms
Speech quality prediction for artificial bandwidth extension algorithms
复制标题
人工带宽扩展算法的语音质量预测
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
P. Alku
中科院分区：
文献类型：
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作者：
Sebastian Möller;Emilia Kelaidi;Friedemann Köster;Nicolas Côté;P. Bauer;T. Fingscheidt;Thomas Schlien;Hannu Pulakka;P. Alku
在窄带到宽带语音传输业务的过渡阶段，人工带宽扩展（Artificial Bandwidth Extension， ABE）算法能够通过扩展音频带宽来减少窄带语音传输信号的感知退化。在本文中，我们分析了使用工具模型是否可以可靠地预测得到的语音质量。将国际电联新标准POLQA、其前身WB-PESQ和诊断DIAL模型的估计与听众的主观判断进行比较。这一比较表明，工具度量并不能完全应对ABE处理的语音，特别是在可靠地预测ABE排序顺序方面。并对其原因及相应的诊断进行了讨论。
During the transition period from narrowband to wideband speech transmission services, Artificial Bandwidth Extension (ABE) algorithms are able to reduce the perceptual degradation of narrowband-transmitted speech signals by extending the audio bandwidth. In this paper, we analyze whether the resulting speech quality can be predicted reliably with instrumental models. Estimations from the new ITU standard POLQA, its predecessor WB-PESQ and the diagnostic DIAL model are compared to subjective listener judgments. This comparison reveals that the instrumental measures are not fully able to cope with ABE-processed speech, particularly in predicting ABE rank orders reliably. Reasons for this finding and corresponding diagnoses are discussed.