NDLI: A single-channel non-intrusive C50 estimator correlated with speech recognition performance

Content Provider	ACM Digital Library
Author	Barreda, Daniel Sharma, Dushyant Van waterschoot, Toon Parada, Pablo Peso Lainez, Jose Naylor, Patrick A.
Copyright Year	2016
Abstract	Several intrusive measures of reverberation can be computed from measured and simulated room impulse responses, over the full frequency band or for each individual mel-frequency subband. It is initially shown that full-band clarity index $C_{50}$ is the most correlated measure on average with reverberant speech recognition performance. This corroborates previous findings but now for the dataset to be used in this study. We extend the previous findings to show that C50 also exhibits the highest mutual information on average. Motivated by these extended findings, a nonintrusive room acoustic (NIRA) estimation method is proposed to estimate C50 from only the reverberant speech signal. The NIRA method is a data-driven approach based on computing a number of features from the speech signal and it employs these features to train a model used to perform the estimation. The choice of features and learning techniques are explored in this work using an evaluation set which comprises approximately 100 000 different reverberant signals (around 93 h of speech) including reverberation from measured and simulated room impulse responses. The feature importance of each feature with respect to the estimation of the target C50 is analysed following two different approaches. In both cases, the newly chosen set of features shows high importance for the target. The best C50 estimator provides a root-mean-square deviation around 3 dB on average for all reverberant test environments.
Starting Page	719
Ending Page	732
Page Count	14
File Format	PDF
ISSN	23299290
e-ISSN	23299304
Volume Number	24
Issue Number	4
Journal	IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-04-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Reverberant speech recognition Reverberation Room acoustic parameter estimation
Content Type	Text
Resource Type	Article
Subject	Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology

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