Effects of Noise, Nonlinear Processing, and Linear Filtering on Perceived Speech Quality

Arehart, Kathryn H.; Kates, James M.; Anderson, Melinda C.

doi:10.1097/aud.0b013e3181d3d4f3

Cited by 35 publications

(39 citation statements)

References 42 publications

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“…Given the literature on the relationship between conjoint analysis and rating scales for measuring preferences (Johnson et al, 2006;Phillips et al, 2002;Ryan et al, 2001), we hypothesized that there would be differences between the two methods in assessing hearing aid preferences (Arehart et al, 2010;Fitzpatrick et al, 2007;Meister et al, 2001;Moeller et al, 2009). This was not in fact the case.…”

Section: Discussionmentioning

confidence: 99%

“…For example, Kochkin (2007) utilizes a 7-point Likert scale in assessing a variety of dimensions of satisfaction. Other examples of Likert or ratings scales include Bagatto et al (Bagatto, Moodie, Seewald, Bartlett, & Scollie, 2011), Arehart et al (Arehart, Kates, & Anderson, 2010), and Moeller et al (Moeller, Hoover, Peterson, & Stelmachowicz, 2009). Conjoint analysis utilizes pairwise comparisons to estimate preferences (Thurstone, 1929).…”

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confidence: 99%

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Consumer Preferences for Hearing Aid Attributes

Bridges

Lataille

Buttorff

et al. 2012

Trends in Amplification

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Low utilization of hearing aids has drawn increased attention to the study of consumer preferences using both simple ratings (e.g., Likert scale) and conjoint analyses, but these two approaches often produce inconsistent results. The study aims to directly compare Likert scales and conjoint analysis in identifying important attributes associated with hearing aids among those with hearing loss. Seven attributes of hearing aids were identified through qualitative research: performance in quiet settings, comfort, feedback, frequency of battery replacement, purchase price, water and sweat resistance, and performance in noisy settings. The preferences of 75 outpatients with hearing loss were measured with both a 5-point Likert scale and with 8 paired-comparison conjoint tasks (the latter being analyzed using OLS [ordinary least squares] and logistic regression). Results were compared by examining implied willingness-to-pay and Pearson’s Rho. A total of 56 respondents (75%) provided complete responses. Two thirds of respondents were male, most had sensorineural hearing loss, and most were older than 50; 44% of respondents had never used a hearing aid. Both methods identified improved performance in noisy settings as the most valued attribute. Respondents were twice as likely to buy a hearing aid with better functionality in noisy environments ( p < .001), and willingness to pay for this attribute ranged from US$2674 on the Likert to US$9000 in the conjoint analysis. The authors find a high level of concordance between the methods—a result that is in stark contrast with previous research. The authors conclude that their result stems from constraining the levels on the Likert scale.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Consumer Preferences for Hearing Aid Attributes

Bridges

Lataille

Buttorff

et al. 2012

Trends in Amplification

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show abstract

“…For instance, Gabrielsson and Sjögren (1979) did an experiment in which participants had to describe the sound of eight different headphones. They found that the headphone with a 10-dB peak in the frequency response at 3 kHz scored strongly on adjectives related to "sharp/hard/loud" and on (Arehart, Kates, & Anderson, 2010) and can improve the threshold of discomfort (Warner & Bentler, 2002). …”

Section: Introductionmentioning

confidence: 99%

A Method to Remove Differences in Frequency Response Between Commercial Hearing Aids to Allow Direct Comparison of the Sound Quality of Hearing-Aid Features

Houben

Brons

Dreschler

2011

Trends in Amplification

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Goal: We want to remove differences in frequency response between different commercial hearing aids so that we can compare the sound quality of signal processing features from different hearing-aid in a future paired-comparison set-up. More specifically, we want to control for the confounding effects of the linear hearing aid response when evaluating nonlinear processing. This article presents a control procedure and evaluates its effectiveness. Method: We increased the similarity of hearing-aid recordings in three steps and used both an objective quality metric and listening tests to investigate if the recordings from different hearing aids were perceptually similar. Results: Neither was it sufficient to manually adjust the hearing-aid insertion gain, nor was it sufficient to add an additional bandwidth limitation to the recordings. Only after the application of an inverse filter the perceptual differences between recordings were removed adequately. Conclusion: It was possible to level the ground between different hearing devices, so to speak. This will allow future research to evaluate the sound quality of nonlinear signal processing features.

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“…Speech quality is affected by factors such as noise and distortion (Kates and Kozma-Spytek, 1994;Arehart et al, 2010). The addition of background noise (e.g., babble noise and machine noise) often leads to deterioration in speech quality (Ramirez et al, 2008;Arehart et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

“…The addition of background noise (e.g., babble noise and machine noise) often leads to deterioration in speech quality (Ramirez et al, 2008;Arehart et al, 2010). The amount of noise is quantified in terms of the signal-to-noise ratio (SNR).…”

Section: Introductionmentioning

confidence: 99%

The effect of noise envelope modulation on quality judgments of noisy speech

Jin

Kates²,

Arehart³

2012

The Journal of the Acoustical Society of America

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This study aims to evaluate how speech quality is affected by noise which varies in modulation from 0% (the lowest correlation with the speech envelope) to 100% (the highest correlation with the speech envelope). Using a scaled paired-comparison forced-choice procedure, ten normal-hearing listeners rated overall preference, noisiness, and distortion of speech stimuli with different noise modulation percentages at 0, 10, and 20 dB signal-to-noise ratios. As noise modulation percentage increased, ratings for overall preference increased, ratings for distortion increased, and ratings for noisiness decreased. The noise modulation effects on quality ratings were significant, even at the same signal-to-noise ratio.

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Effects of Noise, Nonlinear Processing, and Linear Filtering on Perceived Speech Quality

Cited by 35 publications

References 42 publications

Consumer Preferences for Hearing Aid Attributes

Consumer Preferences for Hearing Aid Attributes

A Method to Remove Differences in Frequency Response Between Commercial Hearing Aids to Allow Direct Comparison of the Sound Quality of Hearing-Aid Features

The effect of noise envelope modulation on quality judgments of noisy speech

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