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Using Automatic Speech Recognition to Optimize Hearing-Aid Time Constants
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In: ISSN: 1662-4548 ; EISSN: 1662-453X ; Frontiers in Neuroscience ; https://hal.archives-ouvertes.fr/hal-03627441 ; Frontiers in Neuroscience, Frontiers, 2022, 16 (779062), ⟨10.3389/fnins.2022.779062⟩ ; https://www.frontiersin.org/articles/10.3389/fnins.2022.779062/full (2022)
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RETRIEVING SPEAKER INFORMATION FROM PERSONALIZED ACOUSTIC MODELS FOR SPEECH RECOGNITION
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In: IEEE ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03539741 ; IEEE ICASSP 2022, 2022, Singapour, Singapore (2022)
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Emotional Speech Recognition Using Deep Neural Networks
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In: ISSN: 1424-8220 ; Sensors ; https://hal.archives-ouvertes.fr/hal-03632853 ; Sensors, MDPI, 2022, 22 (4), pp.1414. ⟨10.3390/s22041414⟩ (2022)
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The Impact of Removing Head Movements on Audio-visual Speech Enhancement
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In: ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.inria.fr/hal-03551610 ; ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE Signal Processing Society, May 2022, Singapore, Singapore. pp.1-5 (2022)
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Fine-tuning pre-trained models for Automatic Speech Recognition: experiments on a fieldwork corpus of Japhug (Trans-Himalayan family)
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In: https://halshs.archives-ouvertes.fr/halshs-03647315 ; 2022 (2022)
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Dvoice : An open source dataset for Automatic Speech Recognition on African Languages and Dialects ...
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Abstract:
DVoice is a community initiative that aims to provide African languages and dialects with data and models to facilitate their use of voice technologies. The lack of data on these languages makes it necessary to collect data using methods that are specific to each language. Two different approaches are currently used: the DVoice platform, which is based on Mozilla Common Voice, for collecting authentic recordings from the community, and transfer learning techniques for automatically labeling the recordings. The DVoice platform currently manages 7 languages including Darija (Moroccan Arabic dialect) whose dataset appears on this version, Wolof, Mandingo, Serere, Pular, Diola and Soninke. The Swahili-labeled data present in this version was obtained after automatic labeling via the learning transfer of the Voxlingua107 dataset. For a first time, we also advocate for the increase of data given their small size that we currently have. Thus this version of the dataset contains easily identifiable augmented data. ...
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Keyword:
Artificial Intelligence; Dataset; Speech Recognition; Speech Technologies
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URL: https://zenodo.org/record/6342622 https://dx.doi.org/10.5281/zenodo.6342622
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Dvoice : An open source dataset for Automatic Speech Recognition on African Languages and Dialects ...
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Review on multichannel emotion perception in ASD (Zhang et al., 2022) ...
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Review on multichannel emotion perception in ASD (Zhang et al., 2022) ...
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Towards a Perceptual Model for Estimating the Quality of Visual Speech ...
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An error correction scheme for improved air-tissue boundary in real-time MRI video for speech production ...
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Expression-preserving face frontalization improves visually assisted speech processing ...
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Common Phone: A Multilingual Dataset for Robust Acoustic Modelling ...
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Common Phone: A Multilingual Dataset for Robust Acoustic Modelling ...
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Interactions Among Reverberation, WDRC, and WM (Reinhart & Souza, 2016) ...
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Effects of Spatial Speech Presentation on Listener Response Strategy for Talker-Identification ...
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Detection and Recognition of Asynchronous Auditory/Visual Speech: Effects of Age, Hearing Loss, and Talker Accent ...
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