Author: Jeffrey Forrest HavensPublisher:
ISBN:
Category :
Languages : en
Pages : 314
Book Description
Speech Recognition and Frequency Selectivity for Hearing Impaired Listeners
Author: Jeffrey Forrest HavensPublisher:
ISBN:
Category :
Languages : en
Pages : 314
Book Description
Speech Recognition by the Hearing Impaired
Author: Earleen ElkinsPublisher:
ISBN:
Category : Auditory perception
Languages : en
Pages : 102
Book Description
Aided Speech Recognition in Single-talker Competition by Elderly Hearing-impaired Listeners
Author: Maureen P. CoughlinEarly Development of Children with Hearing Loss
Author: Plural Publishing, IncorporatedPublisher: Plural Publishing
ISBN: 1597567736
Category : Medical
Languages : en
Pages : 361
Book Description
Speech-recognition Abilities with Spectral Compression of Digitally Processed Speech
Author: Deborah J. LekarczykHearing Loss
Author: National Research CouncilPublisher: National Academies Press
ISBN: 0309092965
Category : Social Science
Languages : en
Pages : 321
Book Description
Millions of Americans experience some degree of hearing loss. The Social Security Administration (SSA) operates programs that provide cash disability benefits to people with permanent impairments like hearing loss, if they can show that their impairments meet stringent SSA criteria and their earnings are below an SSA threshold. The National Research Council convened an expert committee at the request of the SSA to study the issues related to disability determination for people with hearing loss. This volume is the product of that study. Hearing Loss: Determining Eligibility for Social Security Benefits reviews current knowledge about hearing loss and its measurement and treatment, and provides an evaluation of the strengths and weaknesses of the current processes and criteria. It recommends changes to strengthen the disability determination process and ensure its reliability and fairness. The book addresses criteria for selection of pure tone and speech tests, guidelines for test administration, testing of hearing in noise, special issues related to testing children, and the difficulty of predicting work capacity from clinical hearing test results. It should be useful to audiologists, otolaryngologists, disability advocates, and others who are concerned with people who have hearing loss.
A Microscopic Model of Speech Recognition for Listeners with Normal and Impaired Hearing
Author: Tim JürgensPublisher:
ISBN: 9783844001471
Category :
Languages : en
Pages : 0
Book Description
This dissertation presents a microscopic model of human speech recognition (HSR), microscopic in a sense that first, the recognition of single phonemes rather than the recognition of whole sentences is modeled. Second, the particular spectro-temporal structure of speech is processed by an auditory model. This contrasts with other models of HSR, which usually use the spectral structure only. The model is capable of predicting phoneme recognition in normal-hearing (NH) listeners in noise along with important aspects of consonant recognition in quiet. Furthermore, this model is extended for the prediction of sentence recognition. The extension is capable of predicting speech recognition of NH and hearing-impaired (HI) listeners as accurately as a standard speech intelligibility model. Parameters reflecting the supra-threshold auditory processing are assessed in NH and HI listeners using psychoacoustical techniques such as forward masking and categorical loudness scaling. These supra-threshold auditory processing deficits are included in the model and the results show that implementing supra-threshold processing improves prediction accuracy. engl.
Speech Recognition in Modulated Noise and Temporal Resolution
Author: Timothy Daniel TrinePublisher:
ISBN:
Category :
Languages : en
Pages : 194
Book Description
Speech Processing in the Auditory System
Author: Steven GreenbergPublisher: Springer Science & Business Media
ISBN: 0387215751
Category : Science
Languages : en
Pages : 487
Book Description
Although speech is the primary behavioral medium by which humans communicate, its auditory basis is poorly understood, having profound implications on efforts to ameliorate the behavioral consequences of hearing impairment and on the development of robust algorithms for computer speech recognition. In this volume, the authors provide an up-to-date synthesis of recent research in the area of speech processing in the auditory system, bringing together a diverse range of scientists to present the subject from an interdisciplinary perspective. Of particular concern is the ability to understand speech in uncertain, potentially adverse acoustic environments, currently the bane of both hearing aid and speech recognition technology. There is increasing evidence that the perceptual stability characteristic of speech understanding is due, at least in part, to elegant transformations of the acoustic signal performed by auditory mechanisms. As a comprehensive review of speech's auditory basis, this book will interest physiologists, anatomists, psychologists, phoneticians, computer scientists, biomedical and electrical engineers, and clinicians.
Improving Speech Intelligibility Without Sacrificing Environmental Sound Recognition
Author: Eric M. JohnsonPublisher:
ISBN:
Category : Hearing disorders
Languages : en
Pages : 0
Book Description
The three manuscripts presented here examine concepts related to speech perception in noise and ways to overcome poor speech intelligibility without depriving listeners of environmental sound recognition. Because of hearing-impaired (HI) listeners’ auditory deficits, there is a substantial need for speech-enhancement (noise reduction) technology. Recent advancements in deep learning have resulted in algorithms that significantly improve the intelligibility of speech in noise, but in order to be suitable for real-world applications such as hearing aids and cochlear implants, these algorithms must be causal, talker independent, corpus independent, and noise independent. Manuscript 1 involves human-subjects testing of a novel, time-domain-based algorithm that fulfills these fundamental requirements. Algorithm processing resulted in significant intelligibility improvements for both HI and normal-hearing (NH) listener groups in each signal-to-noise ratio (SNR) and noise type tested. In Manuscript 2, the range of speech-to-background ratios (SBRs) over which NH and HI listeners can accurately perform both speech and environmental recognition was determined. Separate groups of NH listeners were tested in conditions of selective and divided attention. A single group of HI listeners was tested in the divided attention experiment. Psychometric functions were generated for each listener group and task type. It was found that both NH and HI listeners are capable of high speech intelligibility and high environmental sound recognition over a range of speech-to-background ratios. The range and location of optimal speech-to-background ratios differed across NH and HI listeners. The optimal speech-to-background ratio also depended on the type of environmental sound present. Conventional deep-learning algorithms for speech enhancement target maximum intelligibly by removing as much noise as possible while maintaining the essential characteristics of the target speech signal. Manuscript 3 tests a new form of time-frequency masking that is designed to leave a small amount of background noise intact. The purpose of the unremoved background noise is to allow for environmental sound awareness while still providing significantly increased intelligibility. It was found that this type of processing resulted in significantly improved intelligibility and high environmental sound recognition performance for both types of listeners. It was also found that the same level of maximum attenuation provided the optimal balance of intelligibility and environmental sound recognition for both listener types.