3 papers
cs.CL2025
What do Speech Foundation Models Learn? Analysis and Applications
Ankita Pasad
Speech foundation models (SFMs) are designed to serve as general-purpose representations for a wide range of speech-processing tasks. The last five years have seen an influx of inc…
cs.CL2024
On the Evaluation of Speech Foundation Models for Spoken Language Understanding
Siddhant Arora, Ankita Pasad, Chung-Ming Chien +9
The Spoken Language Understanding Evaluation (SLUE) suite of benchmark tasks was recently introduced to address the need for open resources and benchmarking of complex spoken langu…
cs.CL2024
Self-Supervised Speech Representations are More Phonetic than Semantic
Kwanghee Choi, Ankita Pasad, Tomohiko Nakamura +3
Self-supervised speech models (S3Ms) have become an effective backbone for speech applications. Various analyses suggest that S3Ms encode linguistic properties. In this work, we se…