# Investigation of End-To-End Speaker-Attributed ASR for Continuous Multi-Talker Recordings

arXiv: https://arxiv.org/abs/2008.04546 · HTML: https://mlsanity.com/paper/2008.04546/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Aug 2020.

## Built on by (most cited first, 28 of 28)

- [A Review of Speaker Diarization: Recent Advances with Deep Learning](https://mlsanity.com/paper/2101.09624/) (2021)
- [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)
- [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)
- [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)
- [Summaries, Highlights, and Action items: Design, implementation and evaluation of an LLM-powered meeting recap system](https://mlsanity.com/paper/2307.15793/) (2023)
- [One model to rule them all ? Towards End-to-End Joint Speaker Diarization and Speech Recognition](https://mlsanity.com/paper/2310.01688/) (2023)
- [A Comparative Study of Modular and Joint Approaches for Speaker-Attributed ASR on Monaural Long-Form Audio](https://mlsanity.com/paper/2107.02852/) (2021)
- [Multi-turn RNN-T for streaming recognition of multi-party speech](https://mlsanity.com/paper/2112.10200/) (2021)
- [Generating Data with Text-to-Speech and Large-Language Models for Conversational Speech Recognition](https://mlsanity.com/paper/2408.09215/) (2024)
- [Hypothesis Stitcher for End-to-End Speaker-attributed ASR on Long-form Multi-talker Recordings](https://mlsanity.com/paper/2101.01853/) (2021)
- [Multi-Channel Multi-Speaker ASR Using 3D Spatial Feature](https://mlsanity.com/paper/2111.11023/) (2021)
- [Directed Speech Separation for Automatic Speech Recognition of Long Form Conversational Speech](https://mlsanity.com/paper/2112.05863/) (2021)
- [A Comparative Study on Speaker-attributed Automatic Speech Recognition in Multi-party Meetings](https://mlsanity.com/paper/2203.16834/) (2022)
- [MSA-ASR: Efficient Multilingual Speaker Attribution with frozen ASR Models](https://mlsanity.com/paper/2411.18152/) (2024)
- [TS-SUPERB: A Target Speech Processing Benchmark for Speech Self-Supervised Learning Models](https://mlsanity.com/paper/2505.06660/) (2025)
- [Survey of End-to-End Multi-Speaker Automatic Speech Recognition for Monaural Audio](https://mlsanity.com/paper/2505.10975/) (2025)
- [Separator-Transducer-Segmenter: Streaming Recognition and Segmentation of Multi-party Speech](https://mlsanity.com/paper/2205.05199/) (2022)
- [Improving Speaker Assignment in Speaker-Attributed ASR for Real Meeting Applications](https://mlsanity.com/paper/2403.06570/) (2024)
- [Improved Long-Form Speech Recognition by Jointly Modeling the Primary and Non-primary Speakers](https://mlsanity.com/paper/2312.11123/) (2023)
- [End-to-end multi-talker audio-visual ASR using an active speaker attention module](https://mlsanity.com/paper/2204.00652/) (2022)
- [Towards Word-Level End-to-End Neural Speaker Diarization with Auxiliary Network](https://mlsanity.com/paper/2309.08489/) (2023)
- [A Glance is Enough: Extract Target Sentence By Looking at A keyword](https://mlsanity.com/paper/2310.05352/) (2023)
- [Unsupervised Speaker Diarization in Distributed IoT Networks Using Federated Learning](https://mlsanity.com/paper/2404.10842/) (2024)
- [Hypothesis Clustering and Merging: Novel MultiTalker Speech Recognition with Speaker Tokens](https://mlsanity.com/paper/2409.15732/) (2024)
- [Improving Practical Aspects of End-to-End Multi-Talker Speech Recognition for Online and Offline Scenarios](https://mlsanity.com/paper/2506.14204/) (2025)
- [Leading-Silence Augmentation and Multi-Stage Synthetic Supervision for the Second MLC-SLM Challenge](https://mlsanity.com/paper/2608.14150/) (2026)

## Abstract (arXiv)

Recently, an end-to-end (E2E) speaker-attributed automatic speech recognition (SA-ASR) model was proposed as a joint model of speaker counting, speech recognition and speaker identification for monaural overlapped speech. It showed promising results for simulated speech mixtures consisting of various numbers of speakers. However, the model required prior knowledge of speaker profiles to perform speaker identification, which significantly limited the application of the model. In this paper, we extend the prior work by addressing the case where no speaker profile is available. Specifically, we perform speaker counting and clustering by using the internal speaker representations of the E2E SA-ASR model to diarize the utterances of the speakers whose profiles are missing from the speaker inventory. We also propose a simple modification to the reference labels of the E2E SA-ASR training which helps handle continuous multi-talker recordings well. We conduct a comprehensive investigation of the original E2E SA-ASR and the proposed method on the monaural LibriCSS dataset. Compared to the original E2E SA-ASR with relevant speaker profiles, the proposed method achieves a close performance without any prior speaker knowledge. We also show that the source-target attention in the E2E SA-ASR model provides information about the start and end times of the hypotheses.