Papers by Akshay Raghavan

1 papers
WhiSPA: Semantically and Psychologically Aligned Whisper with Self-Supervised Contrastive and Student-Teacher Learning (2025.acl-long)

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Challenge: Current speech encoding pipelines rely on an additional text-based LM to get robust representations of human communication, even though speech-to-text models often have a LM within.
Approach: They propose to align Whisper's latent space with semantic representations from a text autoencoder and lexically derived embeddings of basic psychological dimensions: emotion and personality.
Outcome: The proposed approach surpasses current speech encoders over self-supervised affective tasks and downstream psychological tasks, achieving an error reduction of 73.4% and 83.8%, respectively.

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