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Found 6 papers, 3 papers with code
Towards Inclusive ASR: Investigating Voice Conversion for Dysarthric Speech Recognition in Low-Resource Languages
Automatic speech recognition (ASR) for dysarthric speech remains challenging due to data scarcity, particularly in non-English languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Speaker- and Text-Independent Estimation of Articulatory Movements and Phoneme Alignments from Speech
This paper introduces a novel combination of two tasks, previously treated separately: acoustic-to-articulatory speech inversion (AAI) and phoneme-to-articulatory (PTA) motion estimation.
Self-Supervised Speech Representations Preserve Speech Characteristics while Anonymizing Voices
Collecting speech data is an important step in training speech recognition systems and other speech-based machine learning models.
Cross-lingual Self-Supervised Speech Representations for Improved Dysarthric Speech Recognition
Compared to using Fbank features, XLSR-based features reduced WERs by 6. 8%, 22. 0%, and 7. 0% for the UASpeech, PC-GITA, and EasyCall corpus, respectively.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Common Phone: A Multilingual Dataset for Robust Acoustic Modelling
A Wav2Vec 2. 0 acoustic model was trained with the Common Phone to perform phonetic symbol recognition and validate the quality of the generated phonetic annotation.
The Phonetic Footprint of Parkinson's Disease
As one of the most prevalent neurodegenerative disorders, Parkinson's disease (PD) has a significant impact on the fine motor skills of patients.
