20 citations · 40 across the 9 of their papers we have counts for
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eess.AS2024★ 5 cited
Scaling Properties of Speech Language Models
Santiago Cuervo, Ricard Marxer
Speech Language Models (SLMs) aim to learn language from raw audio, without textual resources. Despite significant advances, our current models exhibit weak syntax and semantic abi…
eess.AS2024
Transfer Learning from Whisper for Microscopic Intelligibility Prediction
Paul Best, Santiago Cuervo, Ricard Marxer
Macroscopic intelligibility models predict the expected human word-error-rate for a given speech-in-noise stimulus. In contrast, microscopic intelligibility models aim to make fine…
cs.SD2024★ 11 cited
Speech foundation models on intelligibility prediction for hearing-impaired listeners
Santiago Cuervo, Ricard Marxer
Speech foundation models (SFMs) have been benchmarked on many speech processing tasks, often achieving state-of-the-art performance with minimal adaptation. However, the SFM paradi…