SLT 2026 REAL-TSE Challenge: Real-world Target Speaker Extraction from Conversational Recordings
Not on the map. Why?
Abstract (arXiv)
We introduce the REAL-TSE Challenge, an IEEE SLT 2026 satellite challenge on target speaker extraction~(TSE) from real conversational recordings. Given a multi-speaker mixture and one or more enrollment utterances from a target speaker, participating systems must recover only the target speech. Unlike simulated read-speech benchmarks, REAL-TSE evaluates Mandarin and English recordings that contain natural overlap, reverberation, noise, channel mismatch, and conversational dynamics. The challenge defines two complementary tracks: an Online track for low-latency streaming extraction and an Offline track for full-context processing. Systems are evaluated with Token Error Rate (TER), Speaker Similarity (SpkSim), DNSMOS, and target-speaker activity F1. This overview paper describes the task definition, datasets, baselines, evaluation protocol, submitted systems, condition-wise findings, and lessons for future real-world TSE benchmarks.
Key facts. Cited by 2 papers in the map (data through 19 Oct 2026). First posted on arXiv 16 Jul 2026.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2026: 2.
2 papers.