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Deep Speech Representations Track Word Timing along a Low-Dimensional Circular Trajectory
Burin Naowarat, Hao Tang, Sharon Goldwater
Speech timing is fundamental for speech models to recognize words accurately, but how word-timing information is represented in speech models remains underexplored. We study this q…
In-Context Adaptation of Encoder-Decoder Models in Speech Recognition
Yen Meng, Sharon Goldwater, Hao Tang
In-context learning offers an appealing approach to adapt automatic speech recognition (ASR) models to new speakers, accents, and domains by providing speech-text pairs as demonstr…
A framework for analyzing concept representations in neural models
Burin Naowarat, Hao Tang, Sharon Goldwater
Understanding how neural models represent human-interpretable concepts is challenging. Prior work has explored linear concept subspaces from diverse perspectives, such as probing a…
Orthogonality and isotropy of speaker and phonetic information in self-supervised speech representations
Mukhtar Mohamed, Oli Danyi Liu, Hao Tang +1
Self-supervised speech representations can hugely benefit downstream speech technologies, yet the properties that make them useful are still poorly understood. Two candidate proper…
A predictive learning model can simulate temporal dynamics and context effects found in neural representations of continuous speech
Oli Danyi Liu, Hao Tang, Naomi Feldman +1
Speech perception involves storing and integrating sequentially presented items. Recent work in cognitive neuroscience has identified temporal and contextual characteristics in hum…