Dataset Information

Recognition of vocoded words and sentences in quiet and multi-talker babble with children and adults.

ABSTRACT: A vocoder is used to simulate cochlear-implant sound processing in normal-hearing listeners. Typically, there is rapid improvement in vocoded speech recognition, but it is unclear if the improvement rate differs across age groups and speech materials. Children (8-10 years) and young adults (18-26 years) were trained and tested over 2 days (4 hours) on recognition of eight-channel noise-vocoded words and sentences, in quiet and in the presence of multi-talker babble at signal-to-noise ratios of 0, +5, and +10 dB. Children achieved poorer performance than adults in all conditions, for both word and sentence recognition. With training, vocoded speech recognition improvement rates were not significantly different between children and adults, suggesting that improvement in learning how to process speech cues degraded via vocoding is absent of developmental differences across these age groups and types of speech materials. Furthermore, this result confirms that the acutely measured age difference in vocoded speech recognition persists after extended training.

SUBMITTER: Goupell MJ

PROVIDER: S-EPMC7771688 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Recognition of vocoded words and sentences in quiet and multi-talker babble with children and adults.

Goupell Matthew J MJ Draves Garrison T GT Litovsky Ruth Y RY

PloS one 20201229 12

A vocoder is used to simulate cochlear-implant sound processing in normal-hearing listeners. Typically, there is rapid improvement in vocoded speech recognition, but it is unclear if the improvement rate differs across age groups and speech materials. Children (8-10 years) and young adults (18-26 years) were trained and tested over 2 days (4 hours) on recognition of eight-channel noise-vocoded words and sentences, in quiet and in the presence of multi-talker babble at signal-to-noise ratios of 0 ...[more]

PMID: 33373427

Similar Datasets

Project description:Purpose The goal of this study was to determine how various aspects of cognition predict speech recognition ability across different levels of speech vocoding within a single group of listeners. Method We tested the ability of young adults (N = 32) with normal hearing to recognize Perceptually Robust English Sentence Test Open-set (PRESTO) sentences that were degraded with a vocoder to produce different levels of spectral resolution (16, eight, and four carrier channels). Participants also completed tests of cognition (fluid intelligence, short-term memory, and attention), which were used as predictors of sentence recognition. Sentence recognition was compared across vocoder conditions, predictors were correlated with individual differences in sentence recognition, and the relationships between predictors were characterized. Results PRESTO sentence recognition performance declined with a decreasing number of vocoder channels, with no evident floor or ceiling performance in any condition. Individual ability to recognize PRESTO sentences was consistent relative to the group across vocoder conditions. Short-term memory, as measured with serial recall, was a moderate predictor of sentence recognition (ρ = 0.65). Serial recall performance was constant across vocoder conditions when measured with a digit span task. Fluid intelligence was marginally correlated with serial recall, but not sentence recognition. Attentional measures had no discernible relationship to sentence recognition and a marginal relationship with serial recall. Conclusions Verbal serial recall is a substantial predictor of vocoded sentence recognition, and this predictive relationship is independent of spectral resolution. In populations that show variable speech recognition outcomes, such as listeners with cochlear implants, it should be possible to account for the independent effects of spectral resolution and verbal serial recall in their speech recognition ability. Supplemental Material https://doi.org/10.23641/asha.12021051.

Dataset Information

Recognition of vocoded words and sentences in quiet and multi-talker babble with children and adults.

Publications

Recognition of vocoded words and sentences in quiet and multi-talker babble with children and adults.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets