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1
Dataset of British English speech recordings for psychoacoustics and speech processing research: The clarity speech corpus
Graetzer, S.; Akeroyd, M.A.; Barker, J.. - : Elsevier BV, 2022
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2
Dataset of British English speech recordings for psychoacoustics and speech processing research : the Clarity Speech Corpus
Graetzer, SN; Akeroyd, MA; Barker, J. - : Elsevier, 2022
BASE
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3
Autoencoder bottleneck features with multi-task optimisation for improved continuous dysarthric speech recognition
Yue, Z.; Christensen, H.; Barker, J.. - : International Speech Communication Association (ISCA), 2020
BASE
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4
Exploring appropriate acoustic and language modelling choices for continuous dysarthric speech recognition
Yue, Z.; Xiong, F.; Christensen, H.. - : IEEE, 2020
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5
Source domain data selection for improved transfer learning targeting dysarthric speech recognition
Xiong, F.; Barker, J.; Yue, Z.. - : IEEE, 2020
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6
Clarity : machine learning challenges to revolutionise hearing device processing
Porter, E; Cox, TJ; Culling, J. - : European Acoustics Association (EAA)/HAL, 2020
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7
Lexical frequency effects in English and Spanish word misperceptions
Cooke, M.; Garcia Lecumberri, M.L.; Barker, J.. - : Acoustical Society of America, 2019
BASE
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8
A corpus of audio-visual Lombard speech with frontal and profile views
Alghamdi, N.; Maddock, S.; Marxer, R.. - : Acoustical Society of America, 2018
BASE
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9
On the usefulness of the speech phase spectrum for pitch extraction
Loweimi, E.; Barker, J.; Hain, T.. - : ISCA, 2018
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10
The impact of automatic exaggeration of the visual articulatory features of a talker on the intelligibility of spectrally distorted speech
Maddock, S.; Alghamdi, N.; Brown, G.J.. - : Elsevier, 2017
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11
An analysis of environment, microphone and data simulation mismatches in robust speech recognition
Vincent, E.; Watanabe, S.; Nugraha, A.A.. - : Elsevier, 2017
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12
Spectral Reconstruction and Noise Model Estimation Based on a Masking Model for Noise Robust Speech Recognition
Gonzalez, J.A.; Gómez, A.M.; Peinado, A.M.. - : Springer Verlag (Germany), 2017
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13
A data driven approach to audiovisual speech mapping
Abel, A.; Marxer, R.; Barker, J.. - : Springer, 2016
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14
A corpus of noise-induced word misperceptions for English.
Marxer, R.; Garcia Lecumberri, M.L.; Cooke, M.. - : Acoustical Society of America, 2016
BASE
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15
The third 'CHiME' speech separation and recognition challenge: Analysis and outcomes
Barker, J.; Marxer, R.; Vincent, E.. - : Elsevier, 2016
BASE
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16
Source-filter Separation of Speech Signal in the Phase Domain
Loweimi, E.; Barker, J.; Hain, T.. - : ISCA, 2015
BASE
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17
A tropological theory of institutionalization
BASE
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18
Exploiting correlogram structure for robust speech recognition with multiple speech sources
Ma, N.; Green, P.; Barker, J.. - : Elsevier B.V., 2007
BASE
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19
SPECIAL SECTION PAPERS - Mask Estimation for Missing Data Speech Recognition Based on Statistics of Binaural Interaction
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 14 (2006) 1, 58-67
OLC Linguistik
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20
The topology of revolution
In: Communication & cognition. - Gent : Communication & Cognition 36 (2003) 1-2, 61-72
OLC Linguistik
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