# The Speed Submission to DIHARD II: Contributions & Lessons Learned

arXiv: https://arxiv.org/abs/1911.02388 · HTML: https://mlsanity.com/paper/1911.02388/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Nov 2019.

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

- [Online speaker diarization of meetings guided by speech separation](https://mlsanity.com/paper/2402.00067/) (2024)
- [Domain-Dependent Speaker Diarization for the Third DIHARD Challenge](https://mlsanity.com/paper/2101.09884/) (2021)
- [O-EENC-SD: Efficient Online End-to-End Neural Clustering for Speaker Diarization](https://mlsanity.com/paper/2512.15229/) (2025)

## Abstract (arXiv)

This paper describes the speaker diarization systems developed for the Second DIHARD Speech Diarization Challenge (DIHARD II) by the Speed team. Besides describing the system, which considerably outperformed the challenge baselines, we also focus on the lessons learned from numerous approaches that we tried for single and multi-channel systems. We present several components of our diarization system, including categorization of domains, speech enhancement, speech activity detection, speaker embeddings, clustering methods, resegmentation, and system fusion. We analyze and discuss the effect of each such component on the overall diarization performance within the realistic settings of the challenge.