The Effect of Audiovisual and Binaural Listening on the Acceptable Noise Level (ANL): Establishing an ANL Conceptual Model

2014 ◽  
Vol 25 (02) ◽  
pp. 141-153 ◽  
Author(s):  
Yu-Hsiang Wu ◽  
Elizabeth Stangl ◽  
Carol Pang ◽  
Xuyang Zhang

Background: Little is known regarding the acoustic features of a stimulus used by listeners to determine the acceptable noise level (ANL). Features suggested by previous research include speech intelligibility (noise is unacceptable when it degrades speech intelligibility to a certain degree; the intelligibility hypothesis) and loudness (noise is unacceptable when the speech-to-noise loudness ratio is poorer than a certain level; the loudness hypothesis). Purpose: The purpose of the study was to investigate if speech intelligibility or loudness is the criterion feature that determines ANL. To achieve this, test conditions were chosen so that the intelligibility and loudness hypotheses would predict different results. In Experiment 1, the effect of audiovisual (AV) and binaural listening on ANL was investigated; in Experiment 2, the effect of interaural correlation (ρ) on ANL was examined. Research Design: A single-blinded, repeated-measures design was used. Study Sample: Thirty-two and twenty-five younger adults with normal hearing participated in Experiments 1 and 2, respectively. Data Collection and Analysis: In Experiment 1, both ANL and speech recognition performance were measured using the AV version of the Connected Speech Test (CST) in three conditions: AV-binaural, auditory only (AO)-binaural, and AO-monaural. Lipreading skill was assessed using the Utley lipreading test. In Experiment 2, ANL and speech recognition performance were measured using the Hearing in Noise Test (HINT) in three binaural conditions, wherein the interaural correlation of noise was varied: ρ = 1 (NoSo [a listening condition wherein both speech and noise signals are identical across two ears]), −1 (NπSo [a listening condition wherein speech signals are identical across two ears whereas the noise signals of two ears are 180 degrees out of phase]), and 0 (NuSo [a listening condition wherein speech signals are identical across two ears whereas noise signals are uncorrelated across ears]). The results were compared to the predictions made based on the intelligibility and loudness hypotheses. Results: The results of the AV and AO conditions appeared to support the intelligibility hypothesis due to the significant correlation between visual benefit in ANL (AV re: AO ANL) and (1) visual benefit in CST performance (AV re: AO CST) and (2) lipreading skill. The results of the NoSo, NπSo, and NuSo conditions negated the intelligibility hypothesis because binaural processing benefit (NπSo re: NoSo, and NuSo re: NoSo) in ANL was not correlated to that in HINT performance. Instead, the results somewhat supported the loudness hypothesis because the pattern of ANL results across the three conditions (NoSo ≈ NπSo ≈ NuSo ANL) was more consistent with what was predicted by the loudness hypothesis (NoSo ≈ NπSo < NuSo ANL) than by the intelligibility hypothesis (NπSo < NuSo < NoSo ANL). The results of the binaural and monaural conditions supported neither hypothesis because (1) binaural benefit (binaural re: monaural) in ANL was not correlated to that in speech recognition performance, and (2) the pattern of ANL results across conditions (binaural < monaural ANL) was not consistent with the prediction made based on previous binaural loudness summation research (binaural ≥ monaural ANL). Conclusions: The study suggests that listeners may use multiple acoustic features to make ANL judgments. The binaural/monaural results showing that neither hypothesis was supported further indicate that factors other than speech intelligibility and loudness, such as psychological factors, may affect ANL. The weightings of different acoustic features in ANL judgments may vary widely across individuals and listening conditions.

2010 ◽  
Vol 110 (1) ◽  
pp. 31-54 ◽  
Author(s):  
M. Samantha Lewis ◽  
Frederick J. Gallun ◽  
Jane Gordon ◽  
David J. Lilly ◽  
Carl Crandell

2018 ◽  
Vol 27 (4) ◽  
pp. 581-593 ◽  
Author(s):  
Lisa Brody ◽  
Yu-Hsiang Wu ◽  
Elizabeth Stangl

Purpose The aim of this study was to compare the benefit of self-adjusted personal sound amplification products (PSAPs) to audiologist-fitted hearing aids based on speech recognition, listening effort, and sound quality in ecologically relevant test conditions to estimate real-world effectiveness. Method Twenty-five older adults with bilateral mild-to-moderate hearing loss completed the single-blinded, crossover study. Participants underwent aided testing using 3 PSAPs and a traditional hearing aid, as well as unaided testing. PSAPs were adjusted based on participant preference, whereas the hearing aid was configured using best-practice verification protocols. Audibility provided by the devices was quantified using the Speech Intelligibility Index (American National Standards Institute, 2012). Outcome measures assessing speech recognition, listening effort, and sound quality were administered in ecologically relevant laboratory conditions designed to represent real-world speech listening situations. Results All devices significantly improved Speech Intelligibility Index compared to unaided listening, with the hearing aid providing more audibility than all PSAPs. Results further revealed that, in general, the hearing aid improved speech recognition performance and reduced listening effort significantly more than all PSAPs. Few differences in sound quality were observed between devices. All PSAPs improved speech recognition and listening effort compared to unaided testing. Conclusions Hearing aids fitted using best-practice verification protocols were capable of providing more aided audibility, better speech recognition performance, and lower listening effort compared to the PSAPs tested in the current study. Differences in sound quality between the devices were minimal. However, because all PSAPs tested in the study significantly improved participants' speech recognition performance and reduced listening effort compared to unaided listening, PSAPs could serve as a budget-friendly option for those who cannot afford traditional amplification.


2015 ◽  
Vol 26 (05) ◽  
pp. 443-450 ◽  
Author(s):  
Susan Gordon-Hickey ◽  
Holly Morlas

Background: The acceptable noise level (ANL) has been proposed as a prehearing aid fitting measure that could be used for hearing aid selection and counseling purposes. Previous work has demonstrated that a listener’s ANL is unrelated to their speech recognition in noise abilities. It is unknown what criteria a listener uses when they select their ANL. To date, no research has explored the amount of speech recognized at the listener’s ANL. Purpose: To examine the amount of speech recognized at the listener’s ANL to determine whether speech recognition in noise is utilized as a factor for setting ANL. Research Design: A descriptive quasi-experimental study was completed. For all listeners, ANL was measured and speech recognition in noise was tested at ANL and at two additional signal-to-noise ratio (SNR) conditions based on the listener’s ANL (ANL + 5 and ANL – 5). Study Sample: Forty-four older adults served as participants. Twenty-seven participants had normal hearing and seventeen participants had mild to moderately-severe, symmetrical, sensorineural hearing loss. Data Collection and Analysis: Acceptance of noise was calculated from the measures of most comfortable listening level and background noise level. Additionally, speech recognition in noise was assessed at three SNRs using the quick speech-in-noise test materials. Results: A significant interaction effect of SNR condition and ANL group occurred for speech recognition. At ANL, a significant difference in speech recognition in noise was found across groups. Those in the mid and high ANL groups had excellent speech recognition at their ANL. Speech recognition in noise at ANL decreased with ANL category. Conclusions: For listeners with mid and high ANLs, speech recognition appears to play a primary role in setting their ANL. For those with low ANLs, speech recognition may contribute to setting their ANL; however, it does not appear to be the primary determiner of ANL. For those with very low ANLs, speech recognition does not appear to be significant variable for setting their ANL.


1998 ◽  
Vol 107 (3) ◽  
pp. 187-193 ◽  
Author(s):  
Ad F. M. Snik ◽  
Andy J. Beynon ◽  
Catharina T. M. van der Pouw ◽  
Emmanuel A. M. Mylanus ◽  
Cor W. R. J. Cremers

Most, but not all, hearing-impaired patients with air conduction hearing aids prefer binaural amplification instead of monaural amplification. The binaural application of the bone conduction hearing aid is more disputable, because the attenuation (in decibels) of sound waves across the skull is so small (10 dB) that even one bone conduction hearing aid will stimulate both cochleas approximately to the same extent. Binaural fitting of the bone-anchored hearing aid was studied in three experienced bone-anchored hearing aid users. The experiments showed that sound localization, and speech recognition in quiet and also under certain noisy conditions improved significantly with binaural listening compared to the monaural listening condition. On the average, the percentage of correct identifications (within 45°) in the sound localization experiment improved by 53% with binaural listening; the speech reception threshold in quiet improved by 4.4 dB. The binaural advantage in the speech-in-noise test was comparable to that of a control group of subjects with normal hearing listening monaurally versus binaurally. The improvements in the scores were ascribed to diotic summation (improved speech recognition in quiet) and the ability to separate sounds in the binaural listening condition (improved sound localization and improved speech recognition in noise whenever the speech and noise signals came from different directions). All three patients preferred the binaural bone-anchored hearing aids and used them all day.


2019 ◽  
Vol 30 (08) ◽  
pp. 703-711 ◽  
Author(s):  
Alissa Nickerson ◽  
Lisa S. Davidson ◽  
Rosalie M. Uchanski

AbstractAudibility of speech for children with hearing loss (HL) depends on the degree of HL and the fitting of the hearing aids (HAs) themselves. Many studies on cochlear implant (CI) users have demonstrated that preimplant hearing is associated with postimplant outcomes, but there have been very few reports on the fitting of HAs before surgery.The aims of this study were to characterize HA fittings and aided audibility of speech for pediatric HA users with severe to profound HL and to examine the relation between preimplant aided audibility and postimplant speech perception.A descriptive/observational and correlational study. Audiologic records of pediatric CI participants involved in a larger study examining the effects of early acoustic hearing were analyzed retrospectively; when available, these records included HA verification and speech recognition performance.The CI participants were enrolled in audiology centers and oral schools for the deaf across the United States.To determine whether deviations from prescribed DSL target were significantly greater than zero, 95% confidence intervals of the mean deviation were calculated for each frequency (250, 500, 1000, 2000, and 4000 Hz). Correlational analyses were used to examine the relationship between preimplant aided Speech Intelligibility Indices (SIIs) and postimplant speech perception in noise. Correlational analyses were also used to explore the relationship between preimplant aided SIIs and demographic data. T-tests were used to compare preimplant-aided SIIs of HAs of listeners who later became users of either sequential CIs, simultaneous CIs, or bimodal devices.Preimplant fittings of HAs were generally very close to prescriptive targets, except at 4000 Hz for those HAs with active frequency-lowering processing, and preimplant SIIs, albeit low, were correlated with postimplant speech recognition performance in noise. These results suggest that aided audibility should be maximized throughout the HA trial for later speech recognition purposes.It is recommended that HA fittings be optimized to support speech audibility even when considering implantation. In addition to the age at which HA use begins, the aided audibility itself is important in determining CI candidacy and decisions regarding bimodal HA use.


2020 ◽  
Vol 10 (7) ◽  
pp. 2225
Author(s):  
Hwamin Kim ◽  
Jeong-Sik Park

The conventional speech recognition systems can handle the input speech of a specific single language. To realize multi-lingual speech recognition, a language should be firstly identified from input speech. This study proposes an efficient Language IDentification (LID) approach for the multi-lingual system. The standard LID tasks depend on common acoustic features used in speech recognition. However, the features may convey insufficient language-specific information, as they aim to discriminate the general tendency of phonemic information. This study investigates another type of feature characterizing language-specific properties, considering computation complexity. We focus on speech rhythm features providing the prosodic characteristics of speech signals. The rhythm features represent the tendency of consonants and vowels of languages, and therefore, classifying them from speech signals is necessary. For the rapid classification, we employ Gaussian Mixture Model (GMM)-based learning in which two GMMs corresponding to consonants and vowels are firstly trained and used for classifying them. By using the classification results, we estimate the tendency of two phonemic groups such as the duration of consonantal and vocalic intervals and calculate rhythm metrics called R-vector. In experiments on several speech corpora, the automatically extracted R-vector provided similar language tendencies to the conventional studies on linguistics. In addition, the proposed R-vector-based LID approach demonstrated superior or comparable LID performance to the conventional approaches in spite of low computation complexity.


2013 ◽  
Vol 24 (04) ◽  
pp. 307-328 ◽  
Author(s):  
Joshua G.W. Bernstein ◽  
Van Summers ◽  
Elena Grassi ◽  
Ken W. Grant

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.


2019 ◽  
Vol 62 (4) ◽  
pp. 1051-1067 ◽  
Author(s):  
Jonathan H. Venezia ◽  
Allison-Graham Martin ◽  
Gregory Hickok ◽  
Virginia M. Richards

Purpose Age-related sensorineural hearing loss can dramatically affect speech recognition performance due to reduced audibility and suprathreshold distortion of spectrotemporal information. Normal aging produces changes within the central auditory system that impose further distortions. The goal of this study was to characterize the effects of aging and hearing loss on perceptual representations of speech. Method We asked whether speech intelligibility is supported by different patterns of spectrotemporal modulations (STMs) in older listeners compared to young normal-hearing listeners. We recruited 3 groups of participants: 20 older hearing-impaired (OHI) listeners, 19 age-matched normal-hearing listeners, and 10 young normal-hearing (YNH) listeners. Listeners performed a speech recognition task in which randomly selected regions of the speech STM spectrum were revealed from trial to trial. The overall amount of STM information was varied using an up–down staircase to hold performance at 50% correct. Ordinal regression was used to estimate weights showing which regions of the STM spectrum were associated with good performance (a “classification image” or CImg). Results The results indicated that (a) large-scale CImg patterns did not differ between the 3 groups; (b) weights in a small region of the CImg decreased systematically as hearing loss increased; (c) CImgs were also nonsystematically distorted in OHI listeners, and the magnitude of this distortion predicted speech recognition performance even after accounting for audibility; and (d) YNH listeners performed better overall than the older groups. Conclusion We conclude that OHI/older normal-hearing listeners rely on the same speech STMs as YNH listeners but encode this information less efficiently. Supplemental Material https://doi.org/10.23641/asha.7859981


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