Methods › Audio › Speaker Diarization › EEND
End-to-End Neural Diarization
EEND
Introduced by Yusuke Fujita et al. in End-to-End Neural Diarization: Reformulating Speaker Diarization as Simple Multi-label Classification
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
End-to-End Neural Diarization is a neural network for speaker diarization in which a neural network directly outputs speaker diarization results given a multi-speaker recording. To realize such an end-to-end model, the speaker diarization problem is formulated as a multi-label classification problem and a permutation-free objective function is introduced to directly minimize diarization errors. The EEND method can explicitly handle speaker overlaps during training and inference. Just by feeding multi-speaker recordings with corresponding speaker segment labels, the model can be adapted to real conversations.
Papers archive 2025-07-28
26 shown of 26, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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LS-EEND: Long-Form Streaming End-to-End Neural Diarization with Online Attractor Extraction 9 Oct 2024 · 1 repository · arXiv:2410.06670
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From Modular to End-to-End Speaker Diarization 27 Jun 2024 · 0 repositories · arXiv:2407.08752
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Speakers Unembedded: Embedding-free Approach to Long-form Neural Diarization 26 Jun 2024 · 0 repositories · arXiv:2406.18679
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Song Data Cleansing for End-to-End Neural Singer Diarization Using Neural Analysis and Synthesis Framework 24 Jun 2024 · 0 repositories · arXiv:2406.16315
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Powerset multi-class cross entropy loss for neural speaker diarization 19 Oct 2023 · 1 repository · arXiv:2310.13025
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Frame-wise and overlap-robust speaker embeddings for meeting diarization 1 Jun 2023 · 0 repositories · arXiv:2306.00625
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An Experimental Review of Speaker Diarization methods with application to Two-Speaker Conversational Telephone Speech recordings 29 May 2023 · 0 repositories · arXiv:2305.18074
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Neural Diarization with Non-autoregressive Intermediate Attractors 13 Mar 2023 · 1 repository · arXiv:2303.06806
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TOLD: A Novel Two-Stage Overlap-Aware Framework for Speaker Diarization 8 Mar 2023 · 1 repository · arXiv:2303.05397
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BER: Balanced Error Rate For Speaker Diarization 8 Nov 2022 · 2 repositories · arXiv:2211.04304
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Utterance-by-utterance overlap-aware neural diarization with Graph-PIT 28 Jul 2022 · 1 repository · arXiv:2207.13888
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Online Neural Diarization of Unlimited Numbers of Speakers Using Global and Local Attractors 6 Jun 2022 · 0 repositories · arXiv:2206.02432
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Improving the Naturalness of Simulated Conversations for End-to-End Neural Diarization 24 Apr 2022 · 1 repository · arXiv:2204.11232
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Low-Latency Speech Separation Guided Diarization for Telephone Conversations 5 Apr 2022 · 1 repository · arXiv:2204.02306
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From Simulated Mixtures to Simulated Conversations as Training Data for End-to-End Neural Diarization 2 Apr 2022 · 2 repositories · arXiv:2204.00890
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Tight integration of neural- and clustering-based diarization through deep unfolding of infinite Gaussian mixture model 14 Feb 2022 · 0 repositories · arXiv:2202.06524
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ASR-Aware End-to-end Neural Diarization 2 Feb 2022 · 0 repositories · arXiv:2202.01286
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Auxiliary Loss of Transformer with Residual Connection for End-to-End Speaker Diarization 14 Oct 2021 · 0 repositories · arXiv:2110.07116
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Multi-Channel End-to-End Neural Diarization with Distributed Microphones 10 Oct 2021 · 0 repositories · arXiv:2110.04694
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Encoder-Decoder Based Attractors for End-to-End Neural Diarization 20 Jun 2021 · 1 repository · arXiv:2106.10654
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End-to-end Neural Diarization: From Transformer to Conformer 14 Jun 2021 · 0 repositories · arXiv:2106.07167
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Semi-Supervised Training with Pseudo-Labeling for End-to-End Neural Diarization 9 Jun 2021 · 0 repositories · arXiv:2106.04764
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End-to-End Speaker Diarization Conditioned on Speech Activity and Overlap Detection 8 Jun 2021 · 0 repositories · arXiv:2106.04078
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Advances in integration of end-to-end neural and clustering-based diarization for real conversational speech 19 May 2021 · 1 repository · arXiv:2105.09040
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Integrating end-to-end neural and clustering-based diarization: Getting the best of both worlds 26 Oct 2020 · 0 repositories · arXiv:2010.13366
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End-to-End Neural Diarization: Reformulating Speaker Diarization as Simple Multi-label Classification 24 Feb 2020 · 1 repository · arXiv:2003.02966
Tasks archive 2025-07-28
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Usage over time archive 2025-07-28
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Categories archive 2025-07-28
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