A scheme for noise suppression and spectral enhancement of speech to alleviate speech reception problems from loss of frequency selectivity

2002 ◽  
Vol 111 (5) ◽  
pp. 2380
Author(s):  
Johannes Lyzenga ◽  
Joost M. Festen ◽  
Tammo Houtgast
Keyword(s):  
Noise Suppression ◽  
Frequency Selectivity ◽  
Speech Reception ◽  
Spectral Enhancement

Auditory Models of Suprathreshold Distortion and Speech Intelligibility in Persons with Impaired Hearing

2013 ◽  
Vol 24 (04) ◽  
pp. 307-328 ◽  
Author(s):  
Joshua G.W. Bernstein ◽  
Van Summers ◽  
Elena Grassi ◽  
Ken W. Grant
Keyword(s):  
Speech Recognition ◽  
Auditory Processing ◽  
Speech Intelligibility ◽  
Prediction Accuracy ◽  
Dynamic Range ◽  
Recognition Performance ◽  
Frequency Selectivity ◽  
Temporal Acuity ◽  
Dynamic Range Compression ◽  
Speech Reception

Background: Hearing-impaired (HI) individuals with similar ages and audiograms often demonstrate substantial differences in speech-reception performance in noise. Traditional models of speech intelligibility focus primarily on average performance for a given audiogram, failing to account for differences between listeners with similar audiograms. Improved prediction accuracy might be achieved by simulating differences in the distortion that speech may undergo when processed through an impaired ear. Although some attempts to model particular suprathreshold distortions can explain general speech-reception deficits not accounted for by audibility limitations, little has been done to model suprathreshold distortion and predict speech-reception performance for individual HI listeners. Auditory-processing models incorporating individualized measures of auditory distortion, along with audiometric thresholds, could provide a more complete understanding of speech-reception deficits by HI individuals. A computational model capable of predicting individual differences in speech-recognition performance would be a valuable tool in the development and evaluation of hearing-aid signal-processing algorithms for enhancing speech intelligibility. Purpose: This study investigated whether biologically inspired models simulating peripheral auditory processing for individual HI listeners produce more accurate predictions of speech-recognition performance than audiogram-based models. Research Design: Psychophysical data on spectral and temporal acuity were incorporated into individualized auditory-processing models consisting of three stages: a peripheral stage, customized to reflect individual audiograms and spectral and temporal acuity; a cortical stage, which extracts spectral and temporal modulations relevant to speech; and an evaluation stage, which predicts speech-recognition performance by comparing the modulation content of clean and noisy speech. To investigate the impact of different aspects of peripheral processing on speech predictions, individualized details (absolute thresholds, frequency selectivity, spectrotemporal modulation [STM] sensitivity, compression) were incorporated progressively, culminating in a model simulating level-dependent spectral resolution and dynamic-range compression. Study Sample: Psychophysical and speech-reception data from 11 HI and six normal-hearing listeners were used to develop the models. Data Collection and Analysis: Eleven individualized HI models were constructed and validated against psychophysical measures of threshold, frequency resolution, compression, and STM sensitivity. Speech-intelligibility predictions were compared with measured performance in stationary speech-shaped noise at signal-to-noise ratios (SNRs) of −6, −3, 0, and 3 dB. Prediction accuracy for the individualized HI models was compared to the traditional audibility-based Speech Intelligibility Index (SII). Results: Models incorporating individualized measures of STM sensitivity yielded significantly more accurate within-SNR predictions than the SII. Additional individualized characteristics (frequency selectivity, compression) improved the predictions only marginally. A nonlinear model including individualized level-dependent cochlear-filter bandwidths, dynamic-range compression, and STM sensitivity predicted performance more accurately than the SII but was no more accurate than a simpler linear model. Predictions of speech-recognition performance simultaneously across SNRs and individuals were also significantly better for some of the auditory-processing models than for the SII. Conclusions: A computational model simulating individualized suprathreshold auditory-processing abilities produced more accurate speech-intelligibility predictions than the audibility-based SII. Most of this advantage was realized by a linear model incorporating audiometric and STM-sensitivity information. Although more consistent with known physiological aspects of auditory processing, modeling level-dependent changes in frequency selectivity and gain did not result in more accurate predictions of speech-reception performance.

Speech Reception in the Presence of Classroom Noise

1979 ◽  
Vol 10 (4) ◽  
pp. 221-230 ◽  
Author(s):  
Veronica Smyth
Keyword(s):  
Signal To Noise Ratio ◽  
Learning Processes ◽  
Speech Discrimination ◽  
Signal To Noise ◽  
Speech Reception ◽  
Monosyllabic Words ◽  
Noise Ratio

Three hundred children from five to 12 years of age were required to discriminate simple, familiar, monosyllabic words under two conditions: 1) quiet, and 2) in the presence of background classroom noise. Of the sample, 45.3% made errors in speech discrimination in the presence of background classroom noise. The effect was most marked in children younger than seven years six months. The results are discussed considering the signal-to-noise ratio and the possible effects of unwanted classroom noise on learning processes.

Endogenous Noise Suppression During Covert Orienting

2000 ◽  
Author(s):  
Edward Awh ◽  
John Serences ◽  
Kelsey Libner ◽  
Michi Matsukura
Keyword(s):  
Noise Suppression ◽  
Covert Orienting
Sign in / Sign up

Export Citation Format

Share Document