Literature DB >> 24473240

Listening effort and perceived clarity for normal-hearing children with the use of digital noise reduction.

Samantha Gustafson1, Ryan McCreery, Brenda Hoover, Judy G Kopun, Pat Stelmachowicz.   

Abstract

OBJECTIVES: The goal of this study was to evaluate how digital noise reduction (DNR) impacts listening effort and judgment of sound clarity in children with normal hearing. It was hypothesized that when two DNR algorithms differing in signal-to-noise ratio (SNR) output are compared, the algorithm that provides the greatest improvement in overall output SNR will reduce listening effort and receive a better clarity rating from child listeners. A secondary goal was to evaluate the relation between the inversion method measurements and listening effort with DNR processing.
DESIGN: Twenty-four children with normal hearing (ages 7 to 12 years) participated in a speech recognition task in which consonant-vowel-consonant nonwords were presented in broadband background noise. Test stimuli were recorded through two hearing aids with DNR off and DNR on at 0 dB and +5 dB input SNR. Stimuli were presented to listeners and verbal response time (VRT) and phoneme recognition scores were measured. The underlying assumption was that an increase in VRT reflects an increase in listening effort. Children rated the sound clarity for each condition. The two commercially available HAs were chosen based on: (1) an inversion technique, which was used to quantify the magnitude of change in SNR with the activation of DNR, and (2) a measure of magnitude-squared coherence, which was used to ensure that DNR in both devices preserved the spectrum.
RESULTS: One device provided a greater improvement in overall output SNR than the other. Both DNR algorithms resulted in minimal spectral distortion as measured using coherence. For both devices, VRT decreased for the DNR-on condition, suggesting that listening effort decreased with DNR in both devices. Clarity ratings were also better in the DNR-on condition for both devices. The device showing the greatest improvement in output SNR with DNR engaged improved phoneme recognition scores. The magnitude of this improved phoneme recognition was not accurately predicted with measurements of output SNR. Measured output SNR varied in the ability to predict other outcomes.
CONCLUSIONS: Overall, results suggest that DNR effectively reduces listening effort and improves subjective clarity ratings in children with normal hearing but that these improvements are not necessarily related to the output SNR improvements or preserved speech spectra provided by the DNR.

Entities:  

Mesh:

Year:  2014        PMID: 24473240      PMCID: PMC4060443          DOI: 10.1097/01.aud.0000440715.85844.b8

Source DB:  PubMed          Journal:  Ear Hear        ISSN: 0196-0202            Impact factor:   3.570


  48 in total

1.  Measurement of hearing aid internal noise.

Authors:  James D Lewis; Shawn S Goodman; Ruth A Bentler
Journal:  J Acoust Soc Am       Date:  2010-04       Impact factor: 1.840

2.  Assessing the cognitive demands of speech listening for people with hearing losses.

Authors:  B Rakerd; P F Seitz; M Whearty
Journal:  Ear Hear       Date:  1996-04       Impact factor: 3.570

Review 3.  Challenges and recent developments in hearing aids. Part I. Speech understanding in noise, microphone technologies and noise reduction algorithms.

Authors:  King Chung
Journal:  Trends Amplif       Date:  2004

4.  Coherence and the speech intelligibility index.

Authors:  James M Kates; Kathryn H Arehart
Journal:  J Acoust Soc Am       Date:  2005-04       Impact factor: 1.840

5.  Speech understanding in quiet and noise, with and without hearing aids.

Authors:  Mathias Hällgren; Birgitta Larsby; Björn Lyxell; Stig Arlinger
Journal:  Int J Audiol       Date:  2005-10       Impact factor: 2.117

6.  The effect of hearing aid signal-processing schemes on acceptable noise levels: perception and prediction.

Authors:  Yu-Hsiang Wu; Elizabeth Stangl
Journal:  Ear Hear       Date:  2013 May-Jun       Impact factor: 3.570

7.  Effects of noise and working memory capacity on memory processing of speech for hearing-aid users.

Authors:  Elaine Hoi Ning Ng; Mary Rudner; Thomas Lunner; Michael Syskind Pedersen; Jerker Rönnberg
Journal:  Int J Audiol       Date:  2013-04-04       Impact factor: 2.117

8.  Response times to speech stimuli as measures of benefit from amplification.

Authors:  S Gatehouse; J Gordon
Journal:  Br J Audiol       Date:  1990-02

9.  Cognitive load during speech perception in noise: the influence of age, hearing loss, and cognition on the pupil response.

Authors:  Adriana A Zekveld; Sophia E Kramer; Joost M Festen
Journal:  Ear Hear       Date:  2011 Jul-Aug       Impact factor: 3.570

10.  Age-related benefits of digital noise reduction for short-term word learning in children with hearing loss.

Authors:  Andrea Pittman
Journal:  J Speech Lang Hear Res       Date:  2011-06-06       Impact factor: 2.297

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  14 in total

1.  Verbal Response Times as a Potential Indicator of Cognitive Load During Conventional Speech Audiometry With Matrix Sentences.

Authors:  Hartmut Meister; Sebastian Rählmann; Ulrike Lemke; Jana Besser
Journal:  Trends Hear       Date:  2018 Jan-Dec       Impact factor: 3.293

2.  Commentary: listening can be exhausting--fatigue in children and adults with hearing loss.

Authors:  Fred H Bess; Benjamin W Y Hornsby
Journal:  Ear Hear       Date:  2014 Nov-Dec       Impact factor: 3.570

3.  Output signal-to-noise ratio and speech perception in noise: effects of algorithm.

Authors:  Christi W Miller; Ruth A Bentler; Yu-Hsiang Wu; James Lewis; Kelly Tremblay
Journal:  Int J Audiol       Date:  2017-03-30       Impact factor: 2.117

4.  Effects of Noise on Speech Recognition and Listening Effort in Children With Normal Hearing and Children With Mild Bilateral or Unilateral Hearing Loss.

Authors:  Dawna Lewis; Kendra Schmid; Samantha O'Leary; Jody Spalding; Elizabeth Heinrichs-Graham; Robin High
Journal:  J Speech Lang Hear Res       Date:  2016-10-01       Impact factor: 2.297

5.  Interactions Between Digital Noise Reduction and Reverberation: Acoustic and Behavioral Effects.

Authors:  Paul Reinhart; Pavel Zahorik; Pamela Souza
Journal:  J Am Acad Audiol       Date:  2019-07-01       Impact factor: 1.664

6.  Remote Microphone Systems Can Improve Listening-in-Noise Accuracy and Listening Effort for Youth With Autism.

Authors:  Jacob I Feldman; Emily Thompson; Hilary Davis; Bahar Keceli-Kaysili; Kacie Dunham; Tiffany Woynaroski; Anne Marie Tharpe; Erin M Picou
Journal:  Ear Hear       Date:  2022 Mar/Apr       Impact factor: 3.562

7.  Effect of Noise Reduction on Cortical Speech-in-Noise Processing and Its Variance due to Individual Noise Tolerance.

Authors:  Subong Kim; Yu-Hsiang Wu; Hari M Bharadwaj; Inyong Choi
Journal:  Ear Hear       Date:  2022 May/Jun       Impact factor: 3.562

8.  Listening Effort and Speech Recognition with Frequency Compression Amplification for Children and Adults with Hearing Loss.

Authors:  Marc A Brennan; Dawna Lewis; Ryan McCreery; Judy Kopun; Joshua M Alexander
Journal:  J Am Acad Audiol       Date:  2017-10       Impact factor: 1.664

9.  Child-Adult Differences in Using Dual-Task Paradigms to Measure Listening Effort.

Authors:  Erin M Picou; Lauren M Charles; Todd A Ricketts
Journal:  Am J Audiol       Date:  2017-06-13       Impact factor: 1.493

Review 10.  Effects of Hearing Impairment and Hearing Aid Amplification on Listening Effort: A Systematic Review.

Authors:  Barbara Ohlenforst; Adriana A Zekveld; Elise P Jansma; Yang Wang; Graham Naylor; Artur Lorens; Thomas Lunner; Sophia E Kramer
Journal:  Ear Hear       Date:  2017 May/Jun       Impact factor: 3.570

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