SpeechEditBench provides seven atomic editing tasks, compositional multi-operation instructions, and an anchor-based protocol yielding target success, preservation success, and joint success metrics; evaluations show no model excels across dimensions and compositional editing is especially difficult
Plumbley, and Wenwu Wang
3 Pith papers cite this work. Polarity classification is still indexing.
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MMAudioSep adapts a pretrained video-to-audio model via fine-tuning for video/text-queried sound separation, outperforming baselines while preserving generation ability.
citing papers explorer
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SpeechEditBench: A Bilingual Multi-Attribute Benchmark for Instruction-Guided Speech Editing
SpeechEditBench provides seven atomic editing tasks, compositional multi-operation instructions, and an anchor-based protocol yielding target success, preservation success, and joint success metrics; evaluations show no model excels across dimensions and compositional editing is especially difficult
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MMAudioSep: Taming Video-to-Audio Generative Model Towards Video/Text-Queried Sound Separation
MMAudioSep adapts a pretrained video-to-audio model via fine-tuning for video/text-queried sound separation, outperforming baselines while preserving generation ability.
- CodecSep: Prompt-Driven Universal Sound Separation on Neural Audio Codec Latents