Evaluation of speech enhancement algorithms applied to electrolaryngeal speech degraded by noise

Abstract

Electrolaryngeal speech, for persons who have lost their larynx, suffers from the drawback of susceptibility to acoustic noise, which includes inherent electrolarynx motor noise as well as environmental noise. Interactions with electrolarynx users motivated the authors to investigate a crucial drawback of electrolaryngeal speech: degradation of electrolaryngeal speech under noisy environments. The effect of contemporary methods of speech enhancement, viz. noise power spectral density estimation based d-dimensional amplitude trimmed estimation (DATE), and non-negative matrix factorization (NMF) based algorithms, were studied and evaluated for electrolaryngeal speech degraded by noise. Electrolaryngeal speech was corrupted using three types of noisy scenarios at low signal to noise ratios (0, −5 and −10 dB SNR). Objective testing based on the perceptual evaluation of speech quality (PESQ) standard, as well as subjective testing by 14 participants based on the ITU-T P.835 standard were performed. Word-centric intelligibility testing was also performed. The results indicated an improvement in the speech quality. The subjective testing results were further analyzed using one-way analysis of variance (ANOVA) and multiple paired comparison using Tukey’s honest significant difference (HSD) criterion. The overall speech quality of NMF algorithms was found to be significantly higher than that of DATE-based algorithms for the test conditions. The results show that speech enhancement algorithms can aid in improving the electrolaryngeal user experience by reducing the effect of acoustic noise.