AudioSep
Open domain audio source separation model based on natural language query
Product Details
AudioSep is an open-domain audio source separation model based on natural language query. It consists of two key components: text encoder and separation model. We train AudioSep on a large-scale multi-modal dataset and extensively evaluate its capabilities on a number of tasks, including audio event separation, instrument separation, and speech enhancement. AudioSep demonstrates strong separation performance and impressive zero-shot generalization capabilities using audio titles or text labels as queries, significantly outperforming previous sound separation models for audio queries and language queries. To ensure the reproducibility of this work, we will release the source code, evaluation benchmarks, and pretrained models.
Main Features
Target Users
Suitable for the field of audio separation and can be used in audio processing, audio editing and other fields
Examples
Separate guitar sounds in audio using AudioSep
Separate vocals in audio using AudioSep
Separate piano sounds in audio using AudioSep
Quick Access
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