Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Mahmoud Keshavarzi"'
Autor:
Mahmoud Keshavarzi, Marina Salorio-Corbetto, Tobias Reichenbach, Josephine Marriage, Brian C. J. Moore
Publikováno v:
Audiology Research, Vol 14, Iss 2, Pp 264-279 (2024)
Background: The Chear open-set performance test (COPT), which uses a carrier phrase followed by a monosyllabic test word, is intended for clinical assessment of speech recognition, evaluation of hearing-device performance, and the fine-tuning of hear
Externí odkaz:
https://doaj.org/article/1d67387182f8411bb4a79c8bfe5980b1
Autor:
Mahmoud Keshavarzi, Kanad Mandke, Annabel Macfarlane, Lyla Parvez, Fiona Gabrielczyk, Angela Wilson, Usha Goswami
Publikováno v:
NeuroImage: Clinical, Vol 35, Iss , Pp 103054- (2022)
According to the sensory-neural Temporal Sampling theory of developmental dyslexia, neural sampling of auditory information at slow rates (
Externí odkaz:
https://doaj.org/article/1eb13caa8456428ea378c780e66257bb
Autor:
Mahmoud Keshavarzi, Tobias Reichenbach
Publikováno v:
Frontiers in Human Neuroscience, Vol 14 (2020)
Transcranial alternating current stimulation with the speech envelope can modulate the comprehension of speech in noise. The modulation stems from the theta- but not the delta-band portion of the speech envelope, and likely reflects the entrainment o
Externí odkaz:
https://doaj.org/article/7a1d3c4beca144f693482ac681d56a92
Publikováno v:
NeuroImage, Vol 210, Iss , Pp 116557- (2020)
Auditory cortical activity entrains to speech rhythms and has been proposed as a mechanism for online speech processing. In particular, neural activity in the theta frequency band (4–8 Hz) tracks the onset of syllables which may aid the parsing
Externí odkaz:
https://doaj.org/article/2d4368dbfa5f4c87bae9b1b91aae590a
Publikováno v:
Trends in Hearing, Vol 22 (2018)
Despite great advances in hearing-aid technology, users still experience problems with noise in windy environments. The potential benefits of using a deep recurrent neural network (RNN) for reducing wind noise were assessed. The RNN was trained using
Externí odkaz:
https://doaj.org/article/a0f26d99268e4150a319e7bfb42ede66
Autor:
Mahmoud Keshavarzi, Kanad Mandke, Annabel Macfarlane, Lyla Parvez, Fiona Gabrielczyk, Angela Wilson, Usha Goswami
Children with dyslexia are known to show impairments in perceiving speech rhythm, which impact their phonological development. Neural rhythmic speech studies have reported atypical delta phase in children with dyslexia, but beta band effects have not
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::22ebcbc0a451dbdc2bbcfcd3b83a7199
https://doi.org/10.1101/2023.03.29.534542
https://doi.org/10.1101/2023.03.29.534542
Autor:
Mahmoud Keshavarzi, Kanad Mandke, Annabel Macfarlane, Lyla Parvez, Fiona Gabrielczyk, Angela Wilson, Sheila Flanagan, Usha Goswami
The amplitude envelope of speech carries crucial low-frequency acoustic information that assists linguistic decoding. The sensory-neural Temporal Sampling (TS) theory of developmental dyslexia proposes atypical encoding of speech envelope information
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc45f1fc857ab7b4b4ace5b3b1caf7ba
https://www.repository.cam.ac.uk/handle/1810/342567
https://www.repository.cam.ac.uk/handle/1810/342567
Autor:
Mahmoud Keshavarzi, Giovanni M. Di Liberto, Fiona Gabrielczyk, Angela Wilson, Annabel Macfarlane, Usha Goswami
Cross-language data show that children with dyslexia are poor at recognizing syllable stress patterns, yet their speech production appears normal, suggesting an unexpected disconnect between speech input and output processes. Here we utilized a novel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9680b28d5314414dfcff8c8ea04d6cf4
https://doi.org/10.1101/2022.08.24.505144
https://doi.org/10.1101/2022.08.24.505144
Autor:
Mahmoud Keshavarzi, Áine Ní Choisdealbha, Adam Attaheri, Sinead Rocha, Perrine Brusini, Samuel Gibbon, Panagiotis Boutris, Natasha Mead, Helen Olawole-Scott, Henna Ahmed, Sheila A. Flanagan, Kanad Mandke, Usha Goswami
Background: Computational models that successfully decode neural activity into speech are multiplying in the adult literature, with convolutional neural networks (CNNs), backward linear models, and mutual information (MI) models all being applied to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24c9a3e16a23fefc76647675f2cda91e
https://doi.org/10.31234/osf.io/a6qfw
https://doi.org/10.31234/osf.io/a6qfw
Publikováno v:
Trends in Hearing
A deep recurrent neural network (RNN) for reducing transient sounds was developed and its effects on subjective speech intelligibility and listening comfort were investigated. The RNN was trained using sentences spoken with different accents and corr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1d5e7e805df662eadb39c233529add2