Streaming audio-visual target speaker extraction (AVTSE) is essential for latency-sensitive applications. However, current causal systems face two coupled gaps. First, standard benchmarks fix the numb
Falcon is a lightweight causal audio-visual target speaker extraction method that achieves high quality with drastically reduced parameters and latency, supported by the realistic RealSSA benchmark.
Streaming audio-visual target speaker extraction (AVTSE) is essential for latency-sensitive applications. However, current causal systems face two coupled gaps. First, standard benchmarks fix the number of speakers at two and ignore the near-/far-field interference, reverberation, and sudden noise of real scenes. Second, high-performance causal architectures are too heavy for edge deployment. Lightweight alternatives try to reclaim capacity by repeatedly invoking a small separator, which offsets the savings. To address the first gap, we release RealSSA, a realistic AVTSE benchmark consisting of RealSSA-Sim and RealSSA-Real. RealSSA-Sim provides controllable simulated scenes with 1--5…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
Efficient Streaming Audio-Visual Target Speaker Extraction for Real-World Acoustic Scenes was first seen on Hugging Face · Daily papers on Oct 29, 2026. Since then it has appeared in 18 checks on 2 different days. Its best position was #1 of 30, reached on Oct 30, 07:28 UTC. It dropped off the list after Oct 30, 13:28 UTC.
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Not at the moment. It was last on the list on Oct 30, 13:28 UTC, after 2 days of trending.
#1 on Hugging Face · Daily papers, on Oct 30, 07:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 29, 2026 and has been on the list on 2 days (18 checks) since.