Papers with large-scale speech

1 papers
Unlocking Speech Instruction Data Potential with Query Rewriting (2025.findings-acl)

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Challenge: Existing LLMs lack datasets and biased training tasks to follow speech instructions.
Approach: They propose a query rewriting framework that uses multiple agents to annotate and validate the synthesized speech.
Outcome: The proposed framework can transform text instructions into distributions more suitable for TTS models for speech synthesis without human annotation.

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