Assessing the Effect of Temporal Misalignment between the Probe and Processed Speech Signals on Objective Speech Quality Evaluation

Reliable objective speech quality prediction is important for our design of new speech processing and coding algorithms. Many factors may affect the performance of objective speech quality evaluation. Most speech processing algorithms will cause temporal misalignment between the probe and processed (e.g., noise-suppressed) speech signals, which are used as inputs to existing speech quality models. The present work aimed to investigate the effect of temporal misalignment between the two input speech signals on the performance of speech quality evaluation. Subjective speech quality rating data from 120 noise-masked/suppressed conditions (processed by 14 single-channel noise-suppression algorithms) were correlated with existing objective speech quality indices. The probe and processed speech signals were artificially misaligned in a time range up to 50-ms. Results showed that the prediction power of the PESQ measure was not affected by the temporal misalignment effect, mainly due to its embedded temporal alignment processing, while the prediction powers of other quality measures were markedly influenced by the increased temporal misalignment between the two input signals, particularly for the measures of output signal-to-noise ratio. The findings of the present work manifested the importance to compensate the negative temporal misalignment effect for objective speech quality evaluation.