This paper proposes the audio difference explanation task, creates two LLM-generated datasets (ACD and CLD) with three explanation tiers, and presents ADIFF, a prefix-tuning model with cross-projection that beats baselines and Qwen-Audio on the new benchmark.
Selm: Enhancing speech emotion recognition for out-of-domain scenarios
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ADIFF: Explaining audio difference using natural language
This paper proposes the audio difference explanation task, creates two LLM-generated datasets (ACD and CLD) with three explanation tiers, and presents ADIFF, a prefix-tuning model with cross-projection that beats baselines and Qwen-Audio on the new benchmark.