# The Second DISPLACE Challenge : DIarization of SPeaker and LAnguage in Conversational Environments

arXiv: https://arxiv.org/abs/2406.09494 · HTML: https://mlsanity.com/paper/2406.09494/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 36 references that are in the map.
- First posted on arXiv 13 Jun 2024.

## Builds on (most cited first, 19 of 19)

- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)
- [Seamless: Multilingual Expressive and Streaming Speech Translation](https://mlsanity.com/paper/2312.05187/) (2023)
- [CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for Unsegmented Recordings](https://mlsanity.com/paper/2004.09249/) (2020)
- [VoxLingua107: a Dataset for Spoken Language Recognition](https://mlsanity.com/paper/2011.12998/) (2020)
- [Wespeaker: A Research and Production oriented Speaker Embedding Learning Toolkit](https://mlsanity.com/paper/2210.17016/) (2022)
- [Bayesian HMM clustering of x-vector sequences (VBx) in speaker diarization: theory, implementation and analysis on standard tasks](https://mlsanity.com/paper/2012.14952/) (2020)
- [Multilingual and code-switching ASR challenges for low resource Indian languages](https://mlsanity.com/paper/2104.00235/) (2021)
- [Reducing Language confusion for Code-switching Speech Recognition with Token-level Language Diarization](https://mlsanity.com/paper/2210.14567/) (2022)
- [VoxSRC 2020: The Second VoxCeleb Speaker Recognition Challenge](https://mlsanity.com/paper/2012.06867/) (2020)
- [Language-Routing Mixture of Experts for Multilingual and Code-Switching Speech Recognition](https://mlsanity.com/paper/2307.05956/) (2023)
- [MarbleNet: Deep 1D Time-Channel Separable Convolutional Neural Network for Voice Activity Detection](https://mlsanity.com/paper/2010.13886/) (2020)
- [CCC-wav2vec 2.0: Clustering aided Cross Contrastive Self-supervised learning of speech representations](https://mlsanity.com/paper/2210.02592/) (2022)
- [Deep Speaker Embeddings for Far-Field Speaker Recognition on Short Utterances](https://mlsanity.com/paper/2002.06033/) (2020)
- [MERLIon CCS Challenge: A English-Mandarin code-switching child-directed speech corpus for language identification and diarization](https://mlsanity.com/paper/2305.18881/) (2023)
- [PixIT: Joint Training of Speaker Diarization and Speech Separation from Real-world Multi-speaker Recordings](https://mlsanity.com/paper/2403.02288/) (2024)
- [DISPLACE Challenge: DIarization of SPeaker and LAnguage in Conversational Environments](https://mlsanity.com/paper/2303.00830/) (2023)
- [FEARLESS STEPS Challenge (FS-2): Supervised Learning with Massive Naturalistic Apollo Data](https://mlsanity.com/paper/2008.06764/) (2020)
- [Summary of the DISPLACE Challenge 2023 - DIarization of SPeaker and LAnguage in Conversational Environments](https://mlsanity.com/paper/2311.12564/) (2023)
- [Oriental Language Recognition (OLR) 2020: Summary and Analysis](https://mlsanity.com/paper/2107.05365/) (2021)

## Built on by (most cited first, 6 of 6)

- [Indic DiarBench: A Multilingual Joint Diarization and ASR Benchmark for Indian Languages](https://mlsanity.com/paper/2607.23808/) (2026)
- [SAGE-LD: Towards Scalable and Generalizable End-to-End Language Diarization via Simulated Data Augmentation](https://mlsanity.com/paper/2510.00582/) (2025)
- [MUSCAT: MUltilingual, SCientific ConversATion Benchmark](https://mlsanity.com/paper/2604.15929/) (2026)
- [MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition](https://mlsanity.com/paper/2607.24030/) (2026)
- [Code-Switching Detection via Language-Selective Dimensions in Speech Foundation Models](https://mlsanity.com/paper/2610.18726/) (2026)
- [Anuvani-Diarization: Zero Shot Speaker Diarization and Annotation Conventions Across 22 Languages](https://mlsanity.com/paper/2610.20327/) (2026)

## Abstract (arXiv)

The DIarization of SPeaker and LAnguage in Conversational Environments (DISPLACE) 2024 challenge is the second in the series of DISPLACE challenges, which involves tasks of speaker diarization (SD) and language diarization (LD) on a challenging multilingual conversational speech dataset. In the DISPLACE 2024 challenge, we also introduced the task of automatic speech recognition (ASR) on this dataset. The dataset containing 158 hours of speech, consisting of both supervised and unsupervised mono-channel far-field recordings, was released for LD and SD tracks. Further, 12 hours of close-field mono-channel recordings were provided for the ASR track conducted on 5 Indian languages. The details of the dataset, baseline systems and the leader board results are highlighted in this paper. We have also compared our baseline models and the team's performances on evaluation data of DISPLACE-2023 to emphasize the advancements made in this second version of the challenge.