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Parp: Prune, adjust and re-prune for self-supervised speech recognition
Self-supervised speech representation learning (speech SSL) has demonstrated the benefit
of scale in learning rich representations for Automatic Speech Recognition (ASR) with …
of scale in learning rich representations for Automatic Speech Recognition (ASR) with …
How does pre-trained wav2vec 2.0 perform on domain-shifted asr? an extensive benchmark on air traffic control communications
Recent work on self-supervised pre-training focus on leveraging large-scale unlabeled
speech data to build robust end-to-end (E2E) acoustic models (AM) that can be later fine …
speech data to build robust end-to-end (E2E) acoustic models (AM) that can be later fine …
Towards better domain adaptation for self-supervised models: A case study of child ASR
Recently, self-supervised learning (SSL) from unlabelled speech data has gained increased
attention in the automatic speech recognition (ASR) community. Typical SSL methods …
attention in the automatic speech recognition (ASR) community. Typical SSL methods …
DRAFT: A novel framework to reduce domain shifting in self-supervised learning and its application to children's ASR
Self-supervised learning (SSL) in the pretraining stage using un-annotated speech data has
been successful in low-resource automatic speech recognition (ASR) tasks. However …
been successful in low-resource automatic speech recognition (ASR) tasks. However …
Examining the interplay between privacy and fairness for speech processing: A review and perspective
Speech technology has been increasingly deployed in various areas of daily life including
sensitive domains such as healthcare and law enforcement. For these technologies to be …
sensitive domains such as healthcare and law enforcement. For these technologies to be …
A study of gender impact in self-supervised models for speech-to-text systems
Self-supervised models for speech processing emerged recently as popular foundation
blocks in speech processing pipelines. These models are pre-trained on unlabeled audio …
blocks in speech processing pipelines. These models are pre-trained on unlabeled audio …
On the social bias of speech self-supervised models
Self-supervised learning (SSL) speech models have achieved remarkable performance in
various tasks, yet the biased outcomes, especially affecting marginalized groups, raise …
various tasks, yet the biased outcomes, especially affecting marginalized groups, raise …
Pre-trained Speech Processing Models Contain Human-Like Biases that Propagate to Speech Emotion Recognition
Previous work has established that a person's demographics and speech style affect how
well speech processing models perform for them. But where does this bias come from? In …
well speech processing models perform for them. But where does this bias come from? In …
[HTML][HTML] Causal reasoning for algorithmic fairness in voice controlled cyber-physical systems
Automated speaker recognition is enabling personalized interactions with the voice-based
interfaces and assistants part of the modern cyber-physical-social systems. Prior studies …
interfaces and assistants part of the modern cyber-physical-social systems. Prior studies …
Self-supervised speech representations still struggle with african american vernacular english
Underperformance of ASR systems for speakers of African American Vernacular English
(AAVE) and other marginalized language varieties is a well-documented phenomenon, and …
(AAVE) and other marginalized language varieties is a well-documented phenomenon, and …