# STCON System for the CHiME-8 Challenge

arXiv: https://arxiv.org/abs/2410.13411 · HTML: https://mlsanity.com/paper/2410.13411/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Oct 2024.

## Built on by (most cited first, 3 of 3)

- [Unifying Diarization, Separation, and ASR with Multi-Speaker Encoder](https://mlsanity.com/paper/2508.20474/) (2025)
- [Summary of the NOTSOFAR-1 Challenge: Highlights and Learnings](https://mlsanity.com/paper/2501.17304/) (2025)
- [Who Spoke What When? Evaluating Spoken Language Models for Conversational ASR with Semantic and Overlap-Aware Metrics](https://mlsanity.com/paper/2603.22709/) (2026)

## Abstract (arXiv)

This paper describes the STCON system for the CHiME-8 Challenge Task 1 (DASR) aimed at distant automatic speech transcription and diarization with multiple recording devices. Our main attention was paid to carefully trained and tuned diarization pipeline and speaker counting. This allowed to significantly reduce diarization error rate (DER) and obtain more reliable segments for speech separation and recognition. To improve source separation, we designed a Guided Target speaker Extraction (G-TSE) model and used it in conjunction with the traditional Guided Source Separation (GSS) method. To train various parts of our pipeline, we investigated several data augmentation and generation techniques, which helped us to improve the overall system quality.