ORCID Profile
0000-0003-4378-3394
Current Organisation
University of Southampton
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Publisher: Acoustical Society of America (ASA)
Date: 03-2017
DOI: 10.1121/1.4977197
Abstract: Machine-learning based approaches to speech enhancement have recently shown great promise for improving speech intelligibility for hearing-impaired listeners. Here, the performance of three machine-learning algorithms and one classical algorithm, Wiener filtering, was compared. Two algorithms based on neural networks were examined, one using a previously reported feature set and one using a feature set derived from an auditory model. The third machine-learning approach was a dictionary-based sparse-coding algorithm. Speech intelligibility and quality scores were obtained for participants with mild-to-moderate hearing impairments listening to sentences in speech-shaped noise and multi-talker babble following processing with the algorithms. Intelligibility and quality scores were significantly improved by each of the three machine-learning approaches, but not by the classical approach. The largest improvements for both speech intelligibility and quality were found by implementing a neural network using the feature set based on auditory modeling. Furthermore, neural network based techniques appeared more promising than dictionary-based, sparse coding in terms of performance and ease of implementation.
Publisher: SAGE Publications
Date: 29-12-2015
Publisher: Elsevier BV
Date: 02-2017
Publisher: Informa UK Limited
Date: 24-08-2018
DOI: 10.1080/14992027.2017.1367848
Abstract: Processing delay is one of the important factors that limit the development of novel algorithms for hearing devices. In this study, both normal-hearing listeners and listeners with hearing loss were tested for their tolerance of processing delay up to 50 ms using a real-time setup for own-voice and external-voice conditions based on linear processing to avoid confounding effects of time-dependent gain. Participants rated their perceived subjective annoyance for each condition on a 7-point Likert scale. Twenty normal-hearing participants and twenty participants with a range of mild to moderate hearing losses. Delay tolerance was significantly greater for the participants with hearing loss in two out of three voice conditions. The average slopes of annoyance ratings were negatively correlated with the degree of hearing loss across participants. A small trend of higher tolerance of delay by experienced users of hearing aids in comparison to new users was not significant. The increased tolerance of processing delay for speech production and perception with hearing loss and reduced sensitivity to changes in delay with stronger hearing loss may be beneficial for novel algorithms for hearing devices but the setup used in this study differed from commercial hearing aids.
Publisher: IEEE
Date: 03-2016
Publisher: IEEE
Date: 08-2016
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Stefan Bleeck.