Effects of noise suppression on intelligibility: Dependency on signal-to-noise ratios

Hilkhuysen, Gaston; Gaubitch, Nikolay D.; Brookes, Mike; Huckvale, Mark

doi:10.1121/1.3665996

Cited by 35 publications

(35 citation statements)

References 31 publications

(48 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The WSTOI algorithm was evaluated using the results of the intelligibility tests in [11]. Recordings of the IEEE sentences [19] spoken by a single male speaker combined with babble or car noise were played at one of five Signal-to-Noise Ratios (SNRs) to 60 listeners in either an unprocessed condition or after having been processed using one of three noise suppressors.…”

Section: Methodsmentioning

confidence: 99%

A weighted STOI intelligibility metric based on mutual information

Lightburn

Brookes

2016

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Self Cite

View full text Add to dashboard Cite

It is known that the information required for the intelligibility of a speech signal is distributed non-uniformly in time. In this paper we propose WSTOI, a modified version of STOI, a speech intelligibility metric. With WSTOI the contribution of each time-frequency cell is weighted by an estimate of its intelligibility content. This estimate is equal to the mutual information between two hypothetical signals at either end of a simplified model of human communication. Listening tests show that the modification improves the prediction accuracy of STOI at all performance levels on both long and short utterances. An improvement was observed across all tested noise types and suppression algorithms.

show abstract

Section: Methodsmentioning

confidence: 99%

A weighted STOI intelligibility metric based on mutual information

Lightburn

Brookes

2016

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Self Cite

View full text Add to dashboard Cite

show abstract

“…At Signal-to-Noise Ratios (SNRs) below about 0 dB the intelligibility of noisy speech is significantly reduced and conventional speech enhancement techniques are normally unable to improve intelligibility even though they may give substantial improvements in SNR [1,2]. A number of studies [3,4] have shown that the intelligibility of noisy speech can be improved by applying a binary-valued gain mask in the TimeFrequency (TF) domain.…”

Section: Introductionmentioning

confidence: 99%

SOBM - a binary mask for noisy speech that optimises an objective intelligibility metric

Lightburn

Brookes

2015

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Self Cite

View full text Add to dashboard Cite

It is known that the intelligibility of noisy speech can be improved by applying a binary-valued gain mask to a timefrequency representation of the speech. We present the SOBM, an oracle binary mask that maximises STOI, an objective speech intelligibility metric. We show how to determine the SOBM for a deterministic noise signal and also for a stochastic noise signal with a known power spectrum. We demonstrate that applying the SOBM to noisy speech results in a higher predicted intelligibility than is obtained with other masks and show that the stochastic version is robust to mismatch errors in SNR and noise spectrum.

show abstract

“…For an illustration of the performance of current intrusive speech intelligibility techniques we test the STOI method on a database where subjective intelligibility scores are available [62]. The STOI [38], [40] method achieved a Spearman correlation coefficient of 0.94 with subjective word intelligibility scores validating its use for the ADN-TN and additive noise partition of the C-Qual database.…”

Section: B Labelingmentioning

confidence: 99%