Literature DB >> 23275424

Listening effort with cochlear implant simulations.

Carina Pals1, Anastasios Sarampalis, Deniz Baskent.   

Abstract

PURPOSE: Fitting a cochlear implant (CI) for optimal speech perception does not necessarily optimize listening effort. This study aimed to show that listening effort may change between CI processing conditions for which speech intelligibility remains constant.
METHOD: Nineteen normal-hearing participants listened to CI simulations with varying numbers of spectral channels. A dual-task paradigm combining an intelligibility task with either a linguistic or nonlinguistic visual response-time (RT) task measured intelligibility and listening effort. The simultaneously performed tasks compete for limited cognitive resources; changes in effort associated with the intelligibility task are reflected in changes in RT on the visual task. A separate self-report scale provided a subjective measure of listening effort.
RESULTS: All measures showed significant improvements with increasing spectral resolution up to 6 channels. However, only the RT measure of listening effort continued improving up to 8 channels. The effects were stronger for RTs recorded during listening than for RTs recorded between listening.
CONCLUSION: The results suggest that listening effort decreases with increased spectral resolution. Moreover, these improvements are best reflected in objective measures of listening effort, such as RTs on a secondary task, rather than intelligibility scores or subjective effort measures.

Entities:  

Keywords:  cochlear implants; computer simulation; dual task; hearing; listening effort; reaction time; speech perception

Mesh:

Year:  2012        PMID: 23275424     DOI: 10.1044/1092-4388(2012/12-0074)

Source DB:  PubMed          Journal:  J Speech Lang Hear Res        ISSN: 1092-4388            Impact factor:   2.297


  38 in total

1.  Psychometric Functions of Dual-Task Paradigms for Measuring Listening Effort.

Authors:  Yu-Hsiang Wu; Elizabeth Stangl; Xuyang Zhang; Joanna Perkins; Emily Eilers
Journal:  Ear Hear       Date:  2016 Nov/Dec       Impact factor: 3.570

Review 2.  [Bilateral cochlear implants].

Authors:  J Müller
Journal:  HNO       Date:  2017-07       Impact factor: 1.284

3.  Low-frequency fine-structure cues allow for the online use of lexical stress during spoken-word recognition in spectrally degraded speech.

Authors:  Ying-Yee Kong; Alexandra Jesse
Journal:  J Acoust Soc Am       Date:  2017-01       Impact factor: 1.840

4.  Mandarin Tone and Vowel Recognition in Cochlear Implant Users: Effects of Talker Variability and Bimodal Hearing.

Authors:  Yi-Ping Chang; Ronald Y Chang; Chun-Yi Lin; Xin Luo
Journal:  Ear Hear       Date:  2016 May-Jun       Impact factor: 3.570

5.  Accommodation of gender-related phonetic differences by listeners with cochlear implants and in a variety of vocoder simulations.

Authors:  Matthew B Winn
Journal:  J Acoust Soc Am       Date:  2020-01       Impact factor: 1.840

6.  Understanding Speech Amid the Jingle and Jangle: Recommendations for Improving Measurement Practices in Listening Effort Research.

Authors:  Julia F Strand; Lucia Ray; Naseem H Dillman-Hasso; Jed Villanueva; Violet A Brown
Journal:  Audit Percept Cogn       Date:  2021-03-23

7.  Extrinsic Cognitive Load Impairs Spoken Word Recognition in High- and Low-Predictability Sentences.

Authors:  Cynthia R Hunter; David B Pisoni
Journal:  Ear Hear       Date:  2018 Mar/Apr       Impact factor: 3.570

8.  Acoustic richness modulates the neural networks supporting intelligible speech processing.

Authors:  Yune-Sang Lee; Nam Eun Min; Arthur Wingfield; Murray Grossman; Jonathan E Peelle
Journal:  Hear Res       Date:  2015-12-23       Impact factor: 3.208

9.  Listening Effort Measured in Adults with Normal Hearing and Cochlear Implants.

Authors:  Ann E Perreau; Yu-Hsiang Wu; Bailey Tatge; Diana Irwin; Daniel Corts
Journal:  J Am Acad Audiol       Date:  2017-09       Impact factor: 1.664

Review 10.  Neurocognitive factors in sensory restoration of early deafness: a connectome model.

Authors:  Andrej Kral; William G Kronenberger; David B Pisoni; Gerard M O'Donoghue
Journal:  Lancet Neurol       Date:  2016-03-12       Impact factor: 44.182

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