Shared Representation Learning for Reference-Guided Targeted Sound Detection
Human listeners exhibit the remarkable ability to segregate a desired sound from complex acoustic scenes through selective auditory attention, motivating the study of Targeted Sound Detection (TSD). The task requires detecting and localizing a target sound in a mixture when a reference audio of that sound is provided. Prior approaches, rely on generating a sound-discriminative conditional embedding vector for the reference and pairing it with a mixture encoder, jointly optimized with a multi-task learning approach. In this work, we propose a unified encoder architecture that processes both the reference and mixture audio within a shared representation space, promoting stronger alignment w...
| Authors | Shubham Gupta, Adarsh Arigala, B. R. Dilleswari et al. |
|---|---|
| Primary category | eess.AS |
| Published | 17 March 2026 |
| Last updated at source | 17 March 2026 |
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