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2020 – today
- 2025
[j25]Simon Leglaive
, Matthieu Fraticelli, Hend Elghazaly, Léonie Borne, Mostafa Sadeghi, Scott Wisdom, Manuel Pariente, John R. Hershey, Daniel Pressnitzer, Jon P. Barker:
Objective and subjective evaluation of speech enhancement methods in the UDASE task of the 7th CHiME challenge. Comput. Speech Lang. 89: 101685 (2025)- 2024
- [c93]Gerardo Roa Dabike, Michael A. Akeroyd, Scott Bannister, Jon Barker, Trevor J. Cox, Bruno Fazenda, Jennifer Firth, Simone Graetzer, Alinka Greasley, Rebecca R. Vos, William M. Whitmer:
The ICASSP SP Cadenza Challenge: Music Demixing/Remixing for Hearing Aids. ICASSP Workshops 2024: 93-94 - [c92]Rhiannon Mogridge, George Close, Robert Sutherland, Thomas Hain, Jon Barker, Stefan Goetze, Anton Ragni:
Non-Intrusive Speech Intelligibility Prediction for Hearing-Impaired Users Using Intermediate ASR Features and Human Memory Models. ICASSP 2024: 306-310 - [c91]Jon Barker, Michael A. Akeroyd, Will Bailey, Trevor J. Cox, John F. Culling, Jennifer Firth, Simone Graetzer, Graham Naylor:
The 2nd Clarity Prediction Challenge: A Machine Learning Challenge for Hearing Aid Intelligibility Prediction. ICASSP 2024: 11551-11555 - [c90]Max Ehrlich, Jon Barker, Namitha Padmanabhan, Larry Davis, Andrew Tao, Bryan Catanzaro, Abhinav Shrivastava:
Leveraging Bitstream Metadata for Fast, Accurate, Generalized Compressed Video Quality Enhancement. WACV 2024: 1506-1516 - [i25]Rhiannon Mogridge, George Close, Robert Sutherland, Thomas Hain, Jon Barker, Stefan Goetze, Anton Ragni:
Non-Intrusive Speech Intelligibility Prediction for Hearing-Impaired Users using Intermediate ASR Features and Human Memory Models. CoRR abs/2401.13611 (2024) - [i24]Simon Leglaive, Matthieu Fraticelli, Hend Elghazaly, Léonie Borne, Mostafa Sadeghi, Scott Wisdom, Manuel Pariente, John R. Hershey, Daniel Pressnitzer, Jon P. Barker:
Objective and subjective evaluation of speech enhancement methods in the UDASE task of the 7th CHiME challenge. CoRR abs/2402.01413 (2024) - [i23]Robert Sutherland, George Close, Thomas Hain, Stefan Goetze, Jon Barker:
Using Speech Foundational Models in Loss Functions for Hearing Aid Speech Enhancement. CoRR abs/2407.13333 (2024) - [i22]Gerardo Roa Dabike, Michael A. Akeroyd, Scott Bannister, Jon P. Barker, Trevor J. Cox, Bruno Fazenda, Jennifer Firth, Simone Graetzer, Alinka Greasley, Rebecca R. Vos, William M. Whitmer:
The first Cadenza challenges: using machine learning competitions to improve music for listeners with a hearing loss. CoRR abs/2409.05095 (2024) - [i21]Wenliang Dai, Nayeon Lee, Boxin Wang, Zhuoling Yang, Zihan Liu, Jon Barker, Tuomas Rintamaki, Mohammad Shoeybi, Bryan Catanzaro, Wei Ping:
NVLM: Open Frontier-Class Multimodal LLMs. CoRR abs/2409.11402 (2024) - 2023
- [c89]Gerardo Roa Dabike, Scott Bannister, Jennifer Firth, Simone Graetzer, Rebecca R. Vos, Michael A. Akeroyd, Jon Barker, Trevor J. Cox, Bruno Fazenda, Alinka Greasley, William M. Whitmer:
The First Cadenza Signal Processing Challenge: Improving Music for Those With a Hearing Loss. HCMIR@ISMIR 2023 - [c88]Michael A. Akeroyd, Will Bailey, Jon Barker, Trevor J. Cox, John F. Culling, Simone Graetzer, Graham Naylor, Zuzanna Podwinska, Zehai Tu:
The 2nd Clarity Enhancement Challenge for Hearing Aid Speech Intelligibility Enhancement: Overview and Outcomes. ICASSP 2023: 1-5 - [c87]Trevor J. Cox, Jon Barker, Will Bailey, Simone Graetzer, Michael A. Akeroyd, John F. Culling, Graham Naylor:
Overview of the 2023 ICASSP SP Clarity Challenge: Speech Enhancement for Hearing Aids. ICASSP 2023: 1-2 - [i20]Gerardo Roa Dabike, Michael A. Akeroyd, Scott Bannister, Jon Barker, Trevor J. Cox, Bruno Fazenda, Jennifer Firth, Simone Graetzer, Alinka Greasley, Rebecca R. Vos, William M. Whitmer:
The Cadenza ICASSP 2024 Grand Challenge. CoRR abs/2310.03480 (2023) - [i19]Gerardo Roa Dabike, Scott Bannister, Jennifer Firth, Simone Graetzer, Rebecca R. Vos, Michael A. Akeroyd, Jon Barker, Trevor J. Cox, Bruno Fazenda, Alinka Greasley, William M. Whitmer:
The First Cadenza Signal Processing Challenge: Improving Music for Those With a Hearing Loss. CoRR abs/2310.05799 (2023) - [i18]Zehai Tu, Ning Ma, Jon Barker:
Intelligibility prediction with a pretrained noise-robust automatic speech recognition model. CoRR abs/2310.19817 (2023) - [i17]Trevor J. Cox, Jon Barker, Will Bailey, Simone Graetzer, Michael A. Akeroyd, John F. Culling, Graham Naylor:
Overview Of The 2023 Icassp Sp Clarity Challenge: Speech Enhancement For Hearing Aids. CoRR abs/2311.14490 (2023) - 2022
- [j24]Zhengjun Yue, Erfan Loweimi, Heidi Christensen, Jon Barker, Zoran Cvetkovic:
Acoustic Modelling From Raw Source and Filter Components for Dysarthric Speech Recognition. IEEE ACM Trans. Audio Speech Lang. Process. 30: 2968-2980 (2022) - [c86]Jack Deadman, Jon Barker:
Improved Simulation of Realistically-Spatialised Simultaneous Speech Using Multi-Camera Analysis in The Chime-5 Dataset. ICASSP 2022: 591-595 - [c85]Zhengjun Yue, Erfan Loweimi, Zoran Cvetkovic, Heidi Christensen, Jon Barker:
Multi-Modal Acoustic-Articulatory Feature Fusion For Dysarthric Speech Recognition. ICASSP 2022: 7372-7376 - [c84]Zehai Tu, Jack Deadman, Ning Ma, Jon Barker:
Auditory-Based Data Augmentation for end-to-end Automatic Speech Recognition. ICASSP 2022: 7447-7451 - [c83]Zhengjun Yue, Erfan Loweimi, Heidi Christensen, Jon Barker, Zoran Cvetkovic:
Dysarthric Speech Recognition From Raw Waveform with Parametric CNNs. INTERSPEECH 2022: 31-35 - [c82]Jack Deadman, Jon Barker:
Modelling Turn-taking in Multispeaker Parties for Realistic Data Simulation. INTERSPEECH 2022: 266-270 - [c81]Jisi Zhang, Catalin Zorila, Rama Doddipatla, Jon Barker:
On monoaural speech enhancement for automatic recognition of real noisy speech using mixture invariant training. INTERSPEECH 2022: 1056-1060 - [c80]Zehai Tu, Ning Ma, Jon Barker:
Exploiting Hidden Representations from a DNN-based Speech Recogniser for Speech Intelligibility Prediction in Hearing-impaired Listeners. INTERSPEECH 2022: 3488-3492 - [c79]Zehai Tu, Ning Ma, Jon Barker:
Unsupervised Uncertainty Measures of Automatic Speech Recognition for Non-intrusive Speech Intelligibility Prediction. INTERSPEECH 2022: 3493-3497 - [c78]Jon Barker, Michael Akeroyd, Trevor J. Cox, John F. Culling, Jennifer Firth, Simone Graetzer, Holly Griffiths, Lara Harris, Graham Naylor, Zuzanna Podwinska, Eszter Porter, Rhoddy Viveros Muñoz:
The 1st Clarity Prediction Challenge: A machine learning challenge for hearing aid intelligibility prediction. INTERSPEECH 2022: 3508-3512 - [c77]Emma Barker, Jon Barker, Robert J. Gaizauskas, Ning Ma, Monica Lestari Paramita:
SNuC: The Sheffield Numbers Spoken Language Corpus. LREC 2022: 1978-1984 - [i16]Max Ehrlich, Jon Barker, Namitha Padmanabhan, Larry Davis, Andrew Tao, Bryan Catanzaro, Abhinav Shrivastava:
Leveraging Bitstream Metadata for Fast and Accurate Video Compression Correction. CoRR abs/2202.00011 (2022) - [i15]Zehai Tu, Jack Deadman, Ning Ma, Jon Barker:
Auditory-Based Data Augmentation for End-to-End Automatic Speech Recognition. CoRR abs/2204.04284 (2022) - [i14]Zehai Tu, Ning Ma, Jon Barker:
Exploiting Hidden Representations from a DNN-based Speech Recogniser for Speech Intelligibility Prediction in Hearing-impaired Listeners. CoRR abs/2204.04287 (2022) - [i13]Zehai Tu, Ning Ma, Jon Barker:
Unsupervised Uncertainty Measures of Automatic Speech Recognition for Non-intrusive Speech Intelligibility Prediction. CoRR abs/2204.04288 (2022) - [i12]Jisi Zhang, Catalin Zorila, Rama Doddipatla, Jon Barker:
On monoaural speech enhancement for automatic recognition of real noisy speech using mixture invariant training. CoRR abs/2205.01751 (2022) - 2021
- [c76]Zehai Tu, Ning Ma, Jon Barker:
DHASP: Differentiable Hearing Aid Speech Processing. ICASSP 2021: 296-300 - [c75]Jisi Zhang, Catalin Zorila, Rama Doddipatla, Jon Barker:
Time-Domain Speech Extraction with Spatial Information and Multi Speaker Conditioning Mechanism. ICASSP 2021: 6084-6088 - [c74]Gerardo Roa Dabike, Jon Barker:
The use of Voice Source Features for Sung Speech Recognition. ICASSP 2021: 6513-6517 - [c73]Simone Graetzer, Jon Barker, Trevor J. Cox, Michael Akeroyd, John F. Culling, Graham Naylor, Eszter Porter, Rhoddy Viveros Muñoz:
Clarity-2021 Challenges: Machine Learning Challenges for Advancing Hearing Aid Processing. Interspeech 2021: 686-690 - [c72]Zehai Tu, Ning Ma, Jon Barker:
Optimising Hearing Aid Fittings for Speech in Noise with a Differentiable Hearing Loss Model. Interspeech 2021: 691-695 - [c71]Zhengjun Yue, Jon Barker, Heidi Christensen, Cristina McKean, Elaine Ashton, Yvonne Wren, Swapnil Gadgil, Rebecca Bright:
Parental Spoken Scaffolding and Narrative Skills in Crowd-Sourced Storytelling Samples of Young Children. Interspeech 2021: 2946-2950 - [c70]Jisi Zhang, Catalin Zorila, Rama Doddipatla, Jon Barker:
Teacher-Student MixIT for Unsupervised and Semi-Supervised Speech Separation. Interspeech 2021: 3495-3499 - [i11]Jisi Zhang, Catalin Zorila, Rama Doddipatla, Jon Barker:
Time-Domain Speech Extraction with Spatial Information and Multi Speaker Conditioning Mechanism. CoRR abs/2102.03762 (2021) - [i10]Gerardo Roa Dabike, Jon Barker:
The Use of Voice Source Features for Sung Speech Recognition. CoRR abs/2102.10376 (2021) - [i9]Zehai Tu, Ning Ma, Jon Barker:
DHASP: Differentiable Hearing Aid Speech Processing. CoRR abs/2103.08569 (2021) - [i8]Zehai Tu, Ning Ma, Jon Barker:
Optimising Hearing Aid Fittings for Speech in Noise with a Differentiable Hearing Loss Model. CoRR abs/2106.04639 (2021) - [i7]Jisi Zhang, Catalin Zorila, Rama Doddipatla, Jon Barker:
Teacher-Student MixIT for Unsupervised and Semi-supervised Speech Separation. CoRR abs/2106.07843 (2021) - 2020
- [c69]Zhengjun Yue, Feifei Xiong, Heidi Christensen, Jon Barker:
Exploring Appropriate Acoustic and Language Modelling Choices for Continuous Dysarthric Speech Recognition. ICASSP 2020: 6094-6098 - [c68]Jisi Zhang, Catalin Zorila, Rama Doddipatla, Jon Barker:
On End-to-end Multi-channel Time Domain Speech Separation in Reverberant Environments. ICASSP 2020: 6389-6393 - [c67]Feifei Xiong, Jon Barker, Zhengjun Yue, Heidi Christensen:
Source Domain Data Selection for Improved Transfer Learning Targeting Dysarthric Speech Recognition. ICASSP 2020: 7424-7428 - [c66]Jack Deadman, Jon Barker:
Simulating Realistically-Spatialised Simultaneous Speech Using Video-Driven Speaker Detection and the CHiME-5 Dataset. INTERSPEECH 2020: 349-353 - [c65]Zhengjun Yue, Heidi Christensen, Jon Barker:
Autoencoder Bottleneck Features with Multi-Task Optimisation for Improved Continuous Dysarthric Speech Recognition. INTERSPEECH 2020: 4581-4585 - [i6]Shinji Watanabe, Michael I. Mandel, Jon Barker, Emmanuel Vincent:
CHiME-6 Challenge: Tackling Multispeaker Speech Recognition for Unsegmented Recordings. CoRR abs/2004.09249 (2020) - [i5]Jisi Zhang, Catalin Zorila, Rama Doddipatla, Jon Barker:
On End-to-end Multi-channel Time Domain Speech Separation in Reverberant Environments. CoRR abs/2011.05958 (2020)
2010 – 2019
- 2019
- [c64]Feifei Xiong, Jon Barker, Heidi Christensen:
Phonetic Analysis of Dysarthric Speech Tempo and Applications to Robust Personalised Dysarthric Speech Recognition. ICASSP 2019: 5836-5840 - [c63]Gerardo Roa Dabike, Jon Barker:
Automatic Lyric Transcription from Karaoke Vocal Tracks: Resources and a Baseline System. INTERSPEECH 2019: 579-583 - 2018
- [j23]Ricard Marxer, Jon Barker, Najwa Alghamdi, Steve Maddock:
The impact of the Lombard effect on audio and visual speech recognition systems. Speech Commun. 100: 58-68 (2018) - [c62]Feifei Xiong, Jon Barker, Heidi Christensen:
Deep Learning of Articulatory-Based Representations and Applications for Improving Dysarthric Speech Recognition. ITG Symposium on Speech Communication 2018: 1-5 - [c61]Edward Raff, Jon Barker, Jared Sylvester, Robert Brandon, Bryan Catanzaro, Charles K. Nicholas:
Malware Detection by Eating a Whole EXE. AAAI Workshops 2018: 268-276 - [c60]Fitsum A. Reda, Guilin Liu, Kevin J. Shih, Robert Kirby, Jon Barker, David Tarjan, Andrew Tao, Bryan Catanzaro:
SDC-Net: Video Prediction Using Spatially-Displaced Convolution. ECCV (7) 2018: 747-763 - [c59]Erfan Loweimi, Jon Barker, Thomas Hain:
Exploring the Use of Group Delay for Generalised VTS Based Noise Compensation. ICASSP 2018: 4824-4828 - [c58]Erfan Loweimi, Jon Barker, Thomas Hain:
On the Usefulness of the Speech Phase Spectrum for Pitch Extraction. INTERSPEECH 2018: 696-700 - [c57]Jon Barker, Shinji Watanabe, Emmanuel Vincent, Jan Trmal:
The Fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, Task and Baselines. INTERSPEECH 2018: 1561-1565 - [c56]Mandar Gogate, Ahsan Adeel, Ricard Marxer, Jon Barker, Amir Hussain:
DNN Driven Speaker Independent Audio-Visual Mask Estimation for Speech Separation. INTERSPEECH 2018: 2723-2727 - [i4]Jon Barker, Shinji Watanabe, Emmanuel Vincent, Jan Trmal:
The fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, task and baselines. CoRR abs/1803.10609 (2018) - [i3]Mandar Gogate, Ahsan Adeel, Ricard Marxer, Jon Barker, Amir Hussain:
DNN driven Speaker Independent Audio-Visual Mask Estimation for Speech Separation. CoRR abs/1808.00060 (2018) - [i2]Fitsum A. Reda, Guilin Liu, Kevin J. Shih, Robert Kirby, Jon Barker, David Tarjan, Andrew Tao, Bryan Catanzaro:
SDCNet: Video Prediction Using Spatially-Displaced Convolution. CoRR abs/1811.00684 (2018) - 2017
- [j22]Jon Barker, Ricard Marxer, Emmanuel Vincent, Shinji Watanabe:
Multi-microphone speech recognition in everyday environments. Comput. Speech Lang. 46: 386-387 (2017) - [j21]Emmanuel Vincent, Shinji Watanabe, Aditya Arie Nugraha, Jon Barker, Ricard Marxer:
An analysis of environment, microphone and data simulation mismatches in robust speech recognition. Comput. Speech Lang. 46: 535-557 (2017) - [j20]Jon Barker, Ricard Marxer, Emmanuel Vincent, Shinji Watanabe:
The third 'CHiME' speech separation and recognition challenge: Analysis and outcomes. Comput. Speech Lang. 46: 605-626 (2017) - [j19]José A. González, Angel Manuel Gomez Garcia, Antonio M. Peinado, Ning Ma, Jon Barker:
Spectral Reconstruction and Noise Model Estimation Based on a Masking Model for Noise Robust Speech Recognition. Circuits Syst. Signal Process. 36(9): 3731-3760 (2017) - [j18]Najwa Alghamdi, Steve Maddock, Jon Barker, Guy J. Brown:
The impact of automatic exaggeration of the visual articulatory features of a talker on the intelligibility of spectrally distorted speech. Speech Commun. 95: 127-136 (2017) - [c55]Erfan Loweimi, Jon Barker, Thomas Hain:
Statistical normalisation of phase-based feature representation for robust speech recognition. ICASSP 2017: 5310-5314 - [c54]Erfan Loweimi, Jon Barker, Oscar Saz-Torralba, Thomas Hain:
Robust Source-Filter Separation of Speech Signal in the Phase Domain. INTERSPEECH 2017: 414-418 - [c53]Ricard Marxer, Jon Barker:
Binary Mask Estimation Strategies for Constrained Imputation-Based Speech Enhancement. INTERSPEECH 2017: 1988-1992 - [c52]Erfan Loweimi, Jon Barker, Thomas Hain:
Channel Compensation in the Generalised Vector Taylor Series Approach to Robust ASR. INTERSPEECH 2017: 2466-2470 - [p3]Michael I. Mandel, Jon P. Barker:
Multichannel Spatial Clustering Using Model-Based Source Separation. New Era for Robust Speech Recognition, Exploiting Deep Learning 2017: 51-77 - [p2]Jon P. Barker, Ricard Marxer, Emmanuel Vincent, Shinji Watanabe:
The CHiME Challenges: Robust Speech Recognition in Everyday Environments. New Era for Robust Speech Recognition, Exploiting Deep Learning 2017: 327-344 - [i1]Edward Raff, Jon Barker, Jared Sylvester, Robert Brandon, Bryan Catanzaro, Charles K. Nicholas:
Malware Detection by Eating a Whole EXE. CoRR abs/1710.09435 (2017) - 2016
- [c51]Andrew Abel, Ricard Marxer, Jon Barker, Roger Watt, Bill Whitmer, Peter Derleth, Amir Hussain:
A Data Driven Approach to Audiovisual Speech Mapping. BICS 2016: 331-342 - [c50]Máté Attila Tóth, Martin Cooke, Jon Barker:
Misperceptions Arising from Speech-in-Babble Interactions. INTERSPEECH 2016: 630-634 - [c49]María Luisa García Lecumberri, Jon Barker, Ricard Marxer, Martin Cooke:
Language Effects in Noise-Induced Word Misperceptions. INTERSPEECH 2016: 640-644 - [c48]Michael I. Mandel, Jon Barker:
Multichannel Spatial Clustering for Robust Far-Field Automatic Speech Recognition in Mismatched Conditions. INTERSPEECH 2016: 1991-1995 - [c47]Erfan Loweimi, Jon Barker, Thomas Hain:
Use of Generalised Nonlinearity in Vector Taylor Series Noise Compensation for Robust Speech Recognition. INTERSPEECH 2016: 3798-3802 - 2015
- [c46]Ning Ma, Ricard Marxer, Jon Barker, Guy J. Brown:
Exploiting synchrony spectra and deep neural networks for noise-robust automatic speech recognition. ASRU 2015: 490-495 - [c45]Jon Barker, Ricard Marxer, Emmanuel Vincent, Shinji Watanabe:
The third 'CHiME' speech separation and recognition challenge: Dataset, task and baselines. ASRU 2015: 504-511 - [c44]Najwa Alghamdi, Steve Maddock, Guy J. Brown, Jon Barker:
Investigating the impact of artificial enhancement of lip visibility on the intelligibility of spectrally-distorted speech. AVSP 2015: 93-98 - [c43]Najwa Alghamdi, Steve Maddock, Guy J. Brown, Jon Barker:
A comparison of audiovisual and auditory-only training on the perception of spectrally-distorted speech. ICPhS 2015 - [c42]Maryam Al Dabel, Jon Barker:
On the role of discriminative intelligibility model for speech intelligibility enhancement. ICPhS 2015 - [c41]Erfan Loweimi, Jon Barker, Thomas Hain:
Source-filter separation of speech signal in the phase domain. INTERSPEECH 2015: 598-602 - [c40]Lin Lin, Jon Barker, Guy J. Brown:
The effect of cochlear implant processing on speaker intelligibility: a perceptual study and computer model. INTERSPEECH 2015: 1566-1570 - [c39]Ricard Marxer, Martin Cooke, Jon Barker:
A framework for the evaluation of microscopic intelligibility models. INTERSPEECH 2015: 2558-2562 - [c38]Erfan Loweimi, Mortaza Doulaty, Jon Barker, Thomas Hain:
Long-Term Statistical Feature Extraction from Speech Signal and Its Application in Emotion Recognition. SLSP 2015: 173-184 - [c37]Peter Foster, Siddharth Sigtia, Sacha Krstulovic, Jon Barker, Mark D. Plumbley:
Chime-home: A dataset for sound source recognition in a domestic environment. WASPAA 2015: 1-5 - 2014
- [c36]Maryam Al Dabel, Jon Barker:
Speech pre-enhancement using a discriminative microscopic intelligibility model. INTERSPEECH 2014: 2068-2072 - 2013
- [j17]Jon Barker, Emmanuel Vincent:
Special issue on speech separation and recognition in multisource environments. Comput. Speech Lang. 27(3): 619-620 (2013) - [j16]Jon Barker, Emmanuel Vincent, Ning Ma, Heidi Christensen, Phil D. Green:
The PASCAL CHiME speech separation and recognition challenge. Comput. Speech Lang. 27(3): 621-633 (2013) - [j15]Ning Ma, Jon Barker, Heidi Christensen, Phil D. Green:
A hearing-inspired approach for distant-microphone speech recognition in the presence of multiple sources. Comput. Speech Lang. 27(3): 820-836 (2013) - [j14]José L. Carmona, Jon Barker, Angel M. Gomez, Ning Ma:
Speech Spectral Envelope Enhancement by HMM-Based Analysis/Resynthesis. IEEE Signal Process. Lett. 20(6): 563-566 (2013) - [j13]José A. González, Antonio M. Peinado, Ning Ma, Angel M. Gomez, Jon Barker:
MMSE-Based Missing-Feature Reconstruction With Temporal Modeling for Robust Speech Recognition. IEEE Trans. Speech Audio Process. 21(3): 624-635 (2013) - [c35]Emmanuel Vincent, Jon Barker, Shinji Watanabe, Jonathan Le Roux, Francesco Nesta, Marco Matassoni:
The second 'CHiME' speech separation and recognition challenge: An overview of challenge systems and outcomes. ASRU 2013: 162-167 - [c34]Emmanuel Vincent, Jon Barker, Shinji Watanabe, Jonathan Le Roux, Francesco Nesta, Marco Matassoni:
The second 'chime' speech separation and recognition challenge: Datasets, tasks and baselines. ICASSP 2013: 126-130 - 2012
- [j12]Brian Barber, Jon Barker:
Indication of slowly moving ground targets in non-Gaussian clutter using multi-channel synthetic aperture radar. IET Signal Process. 6(5): 424-434 (2012) - [j11]Ning Ma, Jon Barker, Heidi Christensen, Phil D. Green:
Combining Speech Fragment Decoding and Adaptive Noise Floor Modeling. IEEE Trans. Speech Audio Process. 20(3): 818-827 (2012) - [c33]José Andrés González López, Antonio Miguel Peinado Herreros, Angel Manuel Gomez Garcia, Ning Ma, Jon Barker:
Combining missing-data reconstruction and uncertainty decoding for robust speech recognition. ICASSP 2012: 4693-4696 - [c32]Ning Ma, Jon Barker:
Coupling identification and reconstruction of missing features for noise-robust automatic speech recognition. INTERSPEECH 2012: 2638-2641 - [p1]Jon Barker:
Missing-Data Techniques: Recognition with Incomplete Spectrograms. Techniques for Noise Robustness in Automatic Speech Recognition 2012: 369-398 - 2011
- [c31]Juan Andres Morales-Cordovilla, Ning Ma, Victoria E. Sánchez, José L. Carmona, Antonio M. Peinado, Jon Barker:
A pitch based noise estimation technique for robust speech recognition with Missing Data. ICASSP 2011: 4808-4811 - [c30]Ning Ma, Jon Barker, Heidi Christensen, Phil D. Green:
Binaural Cues for Fragment-Based Speech Recognition in Reverberant Multisource Environments. INTERSPEECH 2011: 1657-1660 - [c29]Martin Cooke, Jon Barker, María Luisa García Lecumberri, Krzysztof Wasilewski:
Crowdsourcing for Word Recognition in Noise. INTERSPEECH 2011: 3049-3052 - 2010
- [j10]Jon Barker, Ning Ma, André Coy, Martin Cooke:
Speech fragment decoding techniques for simultaneous speaker identification and speech recognition. Comput. Speech Lang. 24(1): 94-111 (2010) - [c28]Heidi Christensen, Jon Barker:
Speaker turn tracking with mobile microphones: Combining location and pitch information. EUSIPCO 2010: 954-958 - [c27]Ning Ma, Jon Barker, Heidi Christensen, Phil D. Green:
Distant microphone speech recognition in a noisy indoor environment: combining soft missing data and speech fragment decoding. SAPA@INTERSPEECH 2010: 19-24 - [c26]Heidi Christensen, Jon Barker, Ning Ma, Phil D. Green:
The CHiME corpus: a resource and a challenge for computational hearing in multisource environments. INTERSPEECH 2010: 1918-1921
2000 – 2009
- 2009
- [j9]Jon Barker, Xu Shao:
Energetic and Informational Masking Effects in an Audiovisual Speech Recognition System. IEEE Trans. Speech Audio Process. 17(3): 446-458 (2009) - [c25]Heidi Christensen, Ning Ma, Stuart N. Wrigley, Jon Barker:
A speech fragment approach to localising multiple speakers in reverberant environments. ICASSP 2009: 4593-4596 - [c24]Heidi Christensen, Jon Barker:
Using location cues to track speaker changes from mobile, binaural microphones. INTERSPEECH 2009: 140-143 - 2008
- [j8]Xu Shao, Jon Barker:
Stream weight estimation for multistream audio-visual speech recognition in a multispeaker environment. Speech Commun. 50(4): 337-353 (2008) - [c23]Elise Arnaud, Heidi Christensen, Yan-Chen Lu, Jon Barker, Vasil Khalidov, Miles E. Hansard, Bertrand Holveck, Hervé Mathieu, Ramya Narasimha, Elise Taillant, Florence Forbes, Radu Horaud:
The CAVA corpus: synchronised stereoscopic and binaural datasets with head movements. ICMI 2008: 109-116 - 2007
- [j7]André Coy, Jon Barker:
An automatic speech recognition system based on the scene analysis account of auditory perception. Speech Commun. 49(5): 384-401 (2007) - [j6]Jon Barker, Martin Cooke:
Modelling speaker intelligibility in noise. Speech Commun. 49(5): 402-417 (2007) - [j5]Ning Ma, Phil D. Green, Jon Barker, André Coy:
Exploiting correlogram structure for robust speech recognition with multiple speech sources. Speech Commun. 49(12): 874-891 (2007) - [c22]Jon Barker, Xu Shao:
Audio-visual speech fragment decoding. AVSP 2007 - [c21]Ning Ma, Jon Barker, Phil D. Green:
Applying word duration constraints by using unrolled HMMs. INTERSPEECH 2007: 1066-1069 - [c20]Heidi Christensen, Ning Ma, Stuart N. Wrigley, Jon Barker:
Integrating pitch and localisation cues at a speech fragment level. INTERSPEECH 2007: 2769-2772 - 2006
- [j4]Sue Harding, Jon P. Barker, Guy J. Brown:
Mask estimation for missing data speech recognition based on statistics of binaural interaction. IEEE Trans. Speech Audio Process. 14(1): 58-67 (2006) - [c19]Kalle J. Palomäki, Guy J. Brown, Jon P. Barker:
Recognition of Reverberant Speech using Full Cepstral Features and Spectral Missing Data. ICASSP (1) 2006: 289-292 - [c18]Guy J. Brown, Sue Harding, Jon P. Barker:
Speech Separation Based on The Statistics of Binaural Auditory Features. ICASSP (5) 2006: 949-952 - [c17]Jon Barker, André Coy, Ning Ma, Martin Cooke:
Recent advances in speech fragment decoding techniques. INTERSPEECH 2006 - [c16]André Coy, Jon Barker:
A multipitch tracker for monaural speech segmentation. INTERSPEECH 2006 - [c15]Xu Shao, Jon Barker:
Audio-visual speech recognition in the presence of a competing speaker. INTERSPEECH 2006 - 2005
- [j3]Jon P. Barker, Martin P. Cooke, Daniel P. W. Ellis:
Decoding speech in the presence of other sources. Speech Commun. 45(1): 5-25 (2005) - [c14]André Coy, Jon Barker:
Recognising Speech in the Presence of a Competing Speaker using a 'Speech Fragment Decoder'. ICASSP (1) 2005: 425-428 - [c13]Sue Harding, Jon Barker, Guy J. Brown:
Mask Estimation Based on Sound Localisation for Missing Data Speech Recognition. ICASSP (1) 2005: 537-540 - [c12]Jon Barker:
Tracking Facial Markers with an Adaptive Marker Collocation Model. ICASSP (2) 2005: 665-668 - [c11]Sue Harding, Jon P. Barker, Guy J. Brown:
Binaural feature selection for missing data speech recognition. INTERSPEECH 2005: 1269-1272 - [c10]André Coy, Jon Barker:
Soft harmonic masks for recognising speech in the presence of a competing speaker. INTERSPEECH 2005: 2641-2644 - 2004
- [j2]Kalle J. Palomäki, Guy J. Brown, Jon P. Barker:
Techniques for handling convolutional distortion with 'missing data' automatic speech recognition. Speech Commun. 43(1-2): 123-142 (2004) - 2002
- [c9]Kalle J. Palomäki, Guy J. Brown, Jon P. Barker:
Missing data speech recognition in reverberant conditions. ICASSP 2002: 65-68 - 2001
- [c8]Phil D. Green, Jon Barker, Martin Cooke, Ljubomir Josifovski:
Handling Missing and Unreliable Information in Speech Recognition. AISTATS 2001: 112-116 - [c7]Jon Barker, Martin Cooke, Phil D. Green:
Robust ASR based on clean speech models: an evaluation of missing data techniques for connected digit recognition in noise. INTERSPEECH 2001: 213-217 - 2000
- [c6]Jon Barker, Martin Cooke, Daniel P. W. Ellis:
Decoding speech in the presence of other sound sources. INTERSPEECH 2000: 270-273 - [c5]Jon Barker, Ljubomir Josifovski, Martin Cooke, Phil D. Green:
Soft decisions in missing data techniques for robust automatic speech recognition. INTERSPEECH 2000: 373-376
1990 – 1999
- 1999
- [j1]Jon Barker, Martin Cooke:
Is the sine-wave speech cocktail party worth attending? Speech Commun. 27(3-4): 159-174 (1999) - [c4]Jon P. Barker, Frédéric Berthommier:
Estimation of speech acoustics from visual speech features: A comparison of linear and non-linear models. AVSP 1999: 19 - 1998
- [c3]Jon P. Barker, Frédéric Berthommier, Jean-Luc Schwartz:
Is Primitive AV Coherence An Aid To Segment The Scene? AVSP 1998: 103-108 - [c2]Jon Barker, Gethin Williams, Steve Renals:
Acoustic confidence measures for segmenting broadcast news. ICSLP 1998 - 1997
- [c1]Jon Barker, Martin Cooke:
Modelling the recognition of spectrally reduced speech. EUROSPEECH 1997: 2127-2130
Coauthor Index
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