Effects of noise and distortion on speech quality judgments in normal-hearing and hearing-impaired listeners

The masking release (i.e., better speech recognition in fluctuating compared to continuous noise backgrounds) observed for normal-hearing (NH) listeners is generally reduced or absent in hearing-impaired (HI) listeners. One explanation for this lies in the effects of reduced audibility: elevated thresholds may prevent HI listeners from taking advantage of signals available to NH listeners during the dips of temporally fluctuating noise where the interference is relatively weak. This hypothesis was addressed through the development of a signal-processing technique designed to increase the audibility of speech during dips in interrupted noise. This technique acts to (i) compare short-term and long-term estimates of energy, (ii) increase the level of short-term segments whose energy is below the average energy, and (iii) normalize the overall energy of the processed signal to be equivalent to that of the original long-term estimate. Evaluations of this energy-equalizing (EEQ) technique included consonant identification and sentence reception in backgrounds of continuous and regularly interrupted noise. For HI listeners, performance was generally similar for processed and unprocessed signals in continuous noise; however, superior performance for EEQ processing was observed in certain regularly interrupted noise backgrounds.

Section: B Comparison With Other Methodsmentioning

confidence: 99%

Masking release for hearing-impaired listeners: The effect of increased audibility through reduction of amplitude variability

Desloge

Reed

Braida

et al. 2017

“…The present study focused on assessing the impact of these gain-induced (amplification or attenuation) distortions on speech intelligibility in competing talker and steady noise conditions. It does not assess the impact of other unwanted nonlinear distortions introduced in hearing aid instruments by compression or signal clipping (Arehart et al, 2007). Noise-corrupted speech was processed via a conventional noise-reduction algorithm (square-root Wiener filtering) and the gain-induced distortions were confined into one of three regions: Region I containing only attenuation distortion, Region II containing only amplification distortion smaller than 6 dB, and Region III containing amplification distortion in excess of 6 dB.…”

Section: Discussionmentioning

confidence: 99%

“…For that reason, several algorithms have been proposed to minimize speech distortion while constraining the amount of noise distortion introduced to fall below a preset value (Ephraim and Trees, 1995;Chen et al, 2006) or below the auditory masking threshold (Hu and Loizou, 2004). Aside from the distortions introduced by noise-suppression algorithms from inaccuracies in estimating the gain function, hearing aids may also introduce other non-linear distortions such as hard, soft and asymmetrical clipping distortions (Arehart et al, 2007;Tan and Moore, 2008). The perceptual effect of such distortions on intelligibility are not examined in this paper.…”

Section: Introductionmentioning

confidence: 99%

Gain-induced speech distortions and the absence of intelligibility benefit with existing noise-reduction algorithms

Kim

Loizou

2011

Most noise-reduction algorithms used in hearing aids apply a gain to the noisy envelopes to reduce noise interference. The present study assesses the impact of two types of speech distortion introduced by noise-suppressive gain functions: amplification distortion occurring when the amplitude of the target signal is over-estimated, and attenuation distortion occurring when the target amplitude is under-estimated. Sentences corrupted by steady noise and competing talker were processed through a noise-reduction algorithm and synthesized to contain either amplification distortion, attenuation distortion or both. The attenuation distortion was found to have a minimal effect on speech intelligibility. In fact, substantial improvements (> 80 percentage points) in intelligibility, relative to noise-corrupted speech, were obtained when the processed sentences contained only attenuation distortion. When the amplification distortion was limited to be smaller than 6 dB, performance was nearly unaffected in the steady-noise conditions, but was severely degraded in the competing-talker conditions. Overall, the present data suggest that one reason that existing algorithms do not improve speech intelligibility is because they allow amplification distortions in excess of 6 dB. These distortions are shown in this study to be always associated with masker-dominated envelopes and should thus be eliminated.

“…The modified coherence-based SII index (CSII) (Kates and Arehart, 2005) uses the base form of the SII procedure, but with the signal-to-noise ratio term replaced by the signal-to-distortion ratio, which was computed using the coherence function between the input and processed signals. The CSII measures have been used extensively to assess subjective speech quality (Arehart et al, 2007) and speech distortions introduced by hearing aids (Kates, 1992;Kates and Arehart, 2005). These measures have also been shown to yield high correlations with the intelligibility of vocoded speech (Chen and Loizou, 2011a), vocoded and wideband (non-vocoded) Mandarin Chinese (Chen and Loizou, 2011b), and noise-masked speech processed by noise reduction algorithms (Ma et al, 2009).…”

Section: Speech Intelligibility Measuresmentioning

confidence: 99%

Contributions of cochlea-scaled entropy and consonant-vowel boundaries to prediction of speech intelligibility in noise

Chen

Loizou

2012

Recent evidence suggests that spectral change, as measured by cochlea-scaled entropy (CSE), predicts speech intelligibility better than the information carried by vowels or consonants in sentences. Motivated by this finding, the present study investigates whether intelligibility indices implemented to include segments marked with significant spectral change better predict speech intelligibility in noise than measures that include all phonetic segments paying no attention to vowels/consonants or spectral change. The prediction of two intelligibility measures [normalized covariance measure (NCM), coherence-based speech intelligibility index (CSII)] is investigated using three sentencesegmentation methods: relative root-mean-square (RMS) levels, CSE, and traditional phonetic segmentation of obstruents and sonorants. While the CSE method makes no distinction between spectral changes occurring within vowels/consonants, the RMS-level segmentation method places more emphasis on the vowel-consonant boundaries wherein the spectral change is often most prominent, and perhaps most robust, in the presence of noise. Higher correlation with intelligibility scores was obtained when including sentence segments containing a large number of consonant-vowel boundaries than when including segments with highest entropy or segments based on obstruent/sonorant classification. These data suggest that in the context of intelligibility measures the type of spectral change captured by the measure is important.