@inproceedings{d3b6ea826135424f922e5f0cc0beef09,
title = "Subjective and Objective Quality Assessment of Single-Channel Speech Separation Algorithms",
abstract = "Previous studies on performance evaluation of single-channel speech separation (SCSS) algorithms mostly focused on automatic speech recognition (ASR) accuracy as their performance measure. Assessing the separated signals by different metrics other than this has the benefit that the results are expected to carry on to other applications beyond ASR. In this paper, in addition to conventional speech quality metrics (PESQ and SNRloss), we also evaluate the separation systems output using different source separation metrics: blind source separation evaluation (BSS EVAL) and perceptual evaluation methods for audio source separation (PEASS) measures. In our experiments, we apply these measures on the separated signals obtained by two well-known systems in the SCSS challenge to assess the objective and subjective quality of their output signals. Comparing subjective and objective measurements shows that PESQ and PEASS quality metrics predict well the subjective quality of separated signals obtained by the separation systems. From the results it is observed that the short-time objective intelligibility (STOI) measure predict the speech intelligibility results.",
author = "Pejman Mowlaee and Rahim Saeidi and Christensen, {Mads Gr{\ae}sb{\o}ll} and Rainer Martin",
year = "2012",
doi = "10.1109/ICASSP.2012.6287819",
language = "English",
isbn = "978-1-4673-0044-5",
series = "I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings",
publisher = "IEEE Press",
pages = "69--72",
booktitle = "Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on",
note = "2012 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP ; Conference date: 25-03-2012 Through 30-03-2012",
}