Literature DB >> 11831813

The relationship between the intelligibility of time-compressed speech and speech in noise in young and elderly listeners.

Niek J Versfeld1, Wouter A Dreschler.   

Abstract

A conventional measure to determine the ability to understand speech in noisy backgrounds is the so-called speech reception threshold (SRT) for sentences. It yields the signal-to-noise ratio (in dB) for which half of the sentences are correctly perceived. The SRT defines to what degree speech must be audible to a listener in order to become just intelligible. There are indications that elderly listeners have greater difficulty in understanding speech in adverse listening conditions than young listeners. This may be partly due to the differences in hearing sensitivity (presbycusis), hence audibility, but other factors, such as temporal acuity, may also play a significant role. A potential measure for the temporal acuity may be the threshold to which speech can be accelerated, or compressed in time. A new test is introduced where the speech rate is varied adaptively. In analogy to the SRT, the time-compression threshold (or TCT) then is defined as the speech rate (expressed in syllables per second) for which half of the sentences are correctly perceived. In experiment I, the TCT test is introduced and normative data are provided. In experiment II, four groups of subjects (young and elderly normal-hearing and hearing-impaired subjects) participated, and the SRT's in stationary and fluctuating speech-shaped noise were determined, as well as the TCT. The results show that the SRT in fluctuating noise and the TCT are highly correlated. All tests indicate that, even after correction for the hearing loss, elderly normal-hearing subjects perform worse than young normal-hearing subjects. The results indicate that the use of the TCT test or the SRT test in fluctuating noise is preferred over the SRT test in stationary noise.

Entities:  

Mesh:

Year:  2002        PMID: 11831813     DOI: 10.1121/1.1426376

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  23 in total

1.  [Hearing loss determination and assessment of the reduction in earning capacity taking speech discrimination tests in noise into account].

Authors:  C Thiele; H Sukowski; K Wagener; B Kollmeier; T Lenarz; A Lesinski-Schiedat
Journal:  HNO       Date:  2011-11       Impact factor: 1.284

2.  Recovery of functional and structural age-related changes in the rat primary auditory cortex with operant training.

Authors:  Etienne de Villers-Sidani; Loai Alzghoul; Xiaoming Zhou; Kimberly L Simpson; Rick C S Lin; Michael M Merzenich
Journal:  Proc Natl Acad Sci U S A       Date:  2010-07-19       Impact factor: 11.205

3.  Auditory forebrain neurons track temporal features of time-warped natural stimuli.

Authors:  Ross K Maddox; Kamal Sen; Cyrus P Billimoria
Journal:  J Assoc Res Otolaryngol       Date:  2013-10-16

4.  The fluctuating masker benefit for normal-hearing and hearing-impaired listeners with equal audibility at a fixed signal-to-noise ratio.

Authors:  Kenneth Kragh Jensen; Joshua G W Bernstein
Journal:  J Acoust Soc Am       Date:  2019-04       Impact factor: 1.840

5.  The possible role of brain rhythms in perceiving fast speech: Evidence from adult aging.

Authors:  Lana R Penn; Nicole D Ayasse; Arthur Wingfield; Oded Ghitza
Journal:  J Acoust Soc Am       Date:  2018-10       Impact factor: 1.840

6.  Reliability of Measures Intended to Assess Threshold-Independent Hearing Disorders.

Authors:  Aryn M Kamerer; Judy G Kopun; Sara E Fultz; Stephen T Neely; Daniel M Rasetshwane
Journal:  Ear Hear       Date:  2019 Nov/Dec       Impact factor: 3.570

Review 7.  Spatial and temporal processing of single auditory cortical neurons and populations of neurons in the macaque monkey.

Authors:  Gregg H Recanzone; James R Engle; Dina L Juarez-Salinas
Journal:  Hear Res       Date:  2010-04-27       Impact factor: 3.208

8.  Auditory "bubbles": Efficient classification of the spectrotemporal modulations essential for speech intelligibility.

Authors:  Jonathan H Venezia; Gregory Hickok; Virginia M Richards
Journal:  J Acoust Soc Am       Date:  2016-08       Impact factor: 1.840

9.  Decoding time for the identification of musical key.

Authors:  Morwaread M Farbood; Jess Rowland; Gary Marcus; Oded Ghitza; David Poeppel
Journal:  Atten Percept Psychophys       Date:  2015-01       Impact factor: 2.199

10.  Recognizing sequences of sequences.

Authors:  Stefan J Kiebel; Katharina von Kriegstein; Jean Daunizeau; Karl J Friston
Journal:  PLoS Comput Biol       Date:  2009-08-14       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.