# CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for Unsegmented Recordings

arXiv: https://arxiv.org/abs/2004.09249 · HTML: https://mlsanity.com/paper/2004.09249/

## Key facts

- Cited by 132 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Apr 2020.

## Built on by (most cited first, 30 of 132)

- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)
- [A Review of Speaker Diarization: Recent Advances with Deep Learning](https://mlsanity.com/paper/2101.09624/) (2021)
- [BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognition](https://mlsanity.com/paper/2109.13226/) (2021)
- [SpeechStew: Simply Mix All Available Speech Recognition Data to Train One Large Neural Network](https://mlsanity.com/paper/2104.02133/) (2021)
- [Robust Self-Supervised Audio-Visual Speech Recognition](https://mlsanity.com/paper/2201.01763/) (2022)
- [Earnings-21: A Practical Benchmark for ASR in the Wild](https://mlsanity.com/paper/2104.11348/) (2021)
- [Open Source MagicData-RAMC: A Rich Annotated Mandarin Conversational(RAMC) Speech Dataset](https://mlsanity.com/paper/2203.16844/) (2022)
- [Streaming Multi-Talker ASR with Token-Level Serialized Output Training](https://mlsanity.com/paper/2202.00842/) (2022)
- [End-to-End Speaker-Attributed ASR with Transformer](https://mlsanity.com/paper/2104.02128/) (2021)
- [Large-Scale Pre-Training of End-to-End Multi-Talker ASR for Meeting Transcription with Single Distant Microphone](https://mlsanity.com/paper/2103.16776/) (2021)
- [EasyCom: An Augmented Reality Dataset to Support Algorithms for Easy Communication in Noisy Environments](https://mlsanity.com/paper/2107.04174/) (2021)
- [Understanding Sounds, Missing the Questions: The Challenge of Object Hallucination in Large Audio-Language Models](https://mlsanity.com/paper/2406.08402/) (2024)
- [MeetEval: A Toolkit for Computation of Word Error Rates for Meeting Transcription Systems](https://mlsanity.com/paper/2307.11394/) (2023)
- [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)
- [The CHiME-7 DASR Challenge: Distant Meeting Transcription with Multiple Devices in Diverse Scenarios](https://mlsanity.com/paper/2306.13734/) (2023)
- [NOTSOFAR-1 Challenge: New Datasets, Baseline, and Tasks for Distant Meeting Transcription](https://mlsanity.com/paper/2401.08887/) (2024)
- [DiarizationLM: Speaker Diarization Post-Processing with Large Language Models](https://mlsanity.com/paper/2401.03506/) (2024)
- [Towards Neural Diarization for Unlimited Numbers of Speakers Using Global and Local Attractors](https://mlsanity.com/paper/2107.01545/) (2021)
- [Sortformer: A Novel Approach for Permutation-Resolved Speaker Supervision in Speech-to-Text Systems](https://mlsanity.com/paper/2409.06656/) (2024)
- [Streaming Speaker-Attributed ASR with Token-Level Speaker Embeddings](https://mlsanity.com/paper/2203.16685/) (2022)
- [One model to rule them all ? Towards End-to-End Joint Speaker Diarization and Speech Recognition](https://mlsanity.com/paper/2310.01688/) (2023)
- [A Study of Dropout-Induced Modality Bias on Robustness to Missing Video Frames for Audio-Visual Speech Recognition](https://mlsanity.com/paper/2403.04245/) (2024)
- [Multi-scale Speaker Diarization with Dynamic Scale Weighting](https://mlsanity.com/paper/2203.15974/) (2022)
- [Adapting Multi-Lingual ASR Models for Handling Multiple Talkers](https://mlsanity.com/paper/2305.18747/) (2023)
- [Large Language Model Based Generative Error Correction: A Challenge and Baselines for Speech Recognition, Speaker Tagging, and Emotion Recognition](https://mlsanity.com/paper/2409.09785/) (2024)
- [A Comparative Study of Modular and Joint Approaches for Speaker-Attributed ASR on Monaural Long-Form Audio](https://mlsanity.com/paper/2107.02852/) (2021)
- [Advancing Multi-talker ASR Performance with Large Language Models](https://mlsanity.com/paper/2408.17431/) (2024)
- [CrowdSpeech and VoxDIY: Benchmark Datasets for Crowdsourced Audio Transcription](https://mlsanity.com/paper/2107.01091/) (2021)
- [Generating Data with Text-to-Speech and Large-Language Models for Conversational Speech Recognition](https://mlsanity.com/paper/2408.09215/) (2024)
- [Online Neural Diarization of Unlimited Numbers of Speakers Using Global and Local Attractors](https://mlsanity.com/paper/2206.02432/) (2022)

## Abstract (arXiv)

Following the success of the 1st, 2nd, 3rd, 4th and 5th CHiME challenges we organize the 6th CHiME Speech Separation and Recognition Challenge (CHiME-6). The new challenge revisits the previous CHiME-5 challenge and further considers the problem of distant multi-microphone conversational speech diarization and recognition in everyday home environments. Speech material is the same as the previous CHiME-5 recordings except for accurate array synchronization. The material was elicited using a dinner party scenario with efforts taken to capture data that is representative of natural conversational speech. This paper provides a baseline description of the CHiME-6 challenge for both segmented multispeaker speech recognition (Track 1) and unsegmented multispeaker speech recognition (Track 2). Of note, Track 2 is the first challenge activity in the community to tackle an unsegmented multispeaker speech recognition scenario with a complete set of reproducible open source baselines providing speech enhancement, speaker diarization, and speech recognition modules.