# The Second DIHARD Diarization Challenge: Dataset, task, and baselines

arXiv: https://arxiv.org/abs/1906.07839 · HTML: https://mlsanity.com/paper/1906.07839/

## Key facts

- Cited by 39 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jun 2019.

## Built on by (most cited first, 30 of 39)

- [Ego4D: Around the World in 3,000 Hours of Egocentric Video](https://mlsanity.com/paper/2110.07058/) (2021)
- [A Review of Speaker Diarization: Recent Advances with Deep Learning](https://mlsanity.com/paper/2101.09624/) (2021)
- [AVA-AVD: Audio-Visual Speaker Diarization in the Wild](https://mlsanity.com/paper/2111.14448/) (2021)
- [Transcribe-to-Diarize: Neural Speaker Diarization for Unlimited Number of Speakers using End-to-End Speaker-Attributed ASR](https://mlsanity.com/paper/2110.03151/) (2021)
- [Towards Neural Diarization for Unlimited Numbers of Speakers Using Global and Local Attractors](https://mlsanity.com/paper/2107.01545/) (2021)
- [StoryTeller: Improving Long Video Description through Global Audio-Visual Character Identification](https://mlsanity.com/paper/2411.07076/) (2024)
- [BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control Communications](https://mlsanity.com/paper/2110.05781/) (2021)
- [VoxSRC 2022: The Fourth VoxCeleb Speaker Recognition Challenge](https://mlsanity.com/paper/2302.10248/) (2023)
- [The VoxCeleb Speaker Recognition Challenge: A Retrospective](https://mlsanity.com/paper/2408.14886/) (2024)
- [Three-class Overlapped Speech Detection using a Convolutional Recurrent Neural Network](https://mlsanity.com/paper/2104.02878/) (2021)
- [Online Neural Diarization of Unlimited Numbers of Speakers Using Global and Local Attractors](https://mlsanity.com/paper/2206.02432/) (2022)
- [End-to-End Diarization for Variable Number of Speakers with Local-Global Networks and Discriminative Speaker Embeddings](https://mlsanity.com/paper/2105.02096/) (2021)
- [Multi-scale speaker embedding-based graph attention networks for speaker diarisation](https://mlsanity.com/paper/2110.03361/) (2021)
- [Adapting Speaker Embeddings for Speaker Diarisation](https://mlsanity.com/paper/2104.02879/) (2021)
- [Summary of the DISPLACE Challenge 2023 - DIarization of SPeaker and LAnguage in Conversational Environments](https://mlsanity.com/paper/2311.12564/) (2023)
- [Magnitude-aware Probabilistic Speaker Embeddings](https://mlsanity.com/paper/2202.13826/) (2022)
- [The Conversational Short-phrase Speaker Diarization (CSSD) Task: Dataset, Evaluation Metric and Baselines](https://mlsanity.com/paper/2208.08042/) (2022)
- [BER: Balanced Error Rate For Speaker Diarization](https://mlsanity.com/paper/2211.04304/) (2022)
- [Neural Diarization with Non-autoregressive Intermediate Attractors](https://mlsanity.com/paper/2303.06806/) (2023)
- [Spoof Diarization: "What Spoofed When" in Partially Spoofed Audio](https://mlsanity.com/paper/2406.07816/) (2024)
- [A Longitudinal Multi-modal Dataset for Dementia Monitoring and Diagnosis](https://mlsanity.com/paper/2109.01537/) (2021)
- [Speaker Embedding-aware Neural Diarization: an Efficient Framework for Overlapping Speech Diarization in Meeting Scenarios](https://mlsanity.com/paper/2203.09767/) (2022)
- [Joint speech and overlap detection: a benchmark over multiple audio setup and speech domains](https://mlsanity.com/paper/2307.13012/) (2023)
- [Integrating Audio, Visual, and Semantic Information for Enhanced Multimodal Speaker Diarization](https://mlsanity.com/paper/2408.12102/) (2024)
- [Recent Trends in Distant Conversational Speech Recognition: A Review of CHiME-7 and 8 DASR Challenges](https://mlsanity.com/paper/2507.18161/) (2025)
- [Speaker Embedding-aware Neural Diarization for Flexible Number of Speakers with Textual Information](https://mlsanity.com/paper/2111.13694/) (2021)
- [Shennong: a Python toolbox for audio speech features extraction](https://mlsanity.com/paper/2112.05555/) (2021)
- [No-audio speaking status detection in crowded settings via visual pose-based filtering and wearable acceleration](https://mlsanity.com/paper/2211.00549/) (2022)
- [Probabilistic Back-ends for Online Speaker Recognition and Clustering](https://mlsanity.com/paper/2302.09523/) (2023)
- [Lessons Learned in ATCO2: 5000 hours of Air Traffic Control Communications for Robust Automatic Speech Recognition and Understanding](https://mlsanity.com/paper/2305.01155/) (2023)

## Abstract (arXiv)

This paper introduces the second DIHARD challenge, the second in a series of speaker diarization challenges intended to improve the robustness of diarization systems to variation in recording equipment, noise conditions, and conversational domain. The challenge comprises four tracks evaluating diarization performance under two input conditions (single channel vs. multi-channel) and two segmentation conditions (diarization from a reference speech segmentation vs. diarization from scratch). In order to prevent participants from overtuning to a particular combination of recording conditions and conversational domain, recordings are drawn from a variety of sources ranging from read audiobooks to meeting speech, to child language acquisition recordings, to dinner parties, to web video. We describe the task and metrics, challenge design, datasets, and baseline systems for speech enhancement, speech activity detection, and diarization.