# Audio-WestlakeU/FS-EEND

<https://repo.masters-masters.com/en/repos/Audio-WestlakeU/FS-EEND>

[Home](https://repo.masters-masters.com/en) › [Audio-WestlakeU](https://repo.masters-masters.com/en/owners/Audio-WestlakeU) › [FS-EEND](https://repo.masters-masters.com/en/repos/Audio-WestlakeU/FS-EEND)

Audio-WestlakeU/FS-EEND has 192 stars on GitHub. Its RepoMasters card: Prototype tier. The official Pytorch implementation of "Frame-wise streaming end-to-end…

| Field | Value |
| --- | --- |
| Owner | [Audio-WestlakeU](https://repo.masters-masters.com/en/owners/Audio-WestlakeU) |
| Stars | 192 |
| Forks | 19 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2023 |
| Topics | online-inference, speaker-diarization, frame-wise, self-attention, end-to-end, pytorch, long-form |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [Audio-WestlakeU/FS-EEND](https://github.com/Audio-WestlakeU/FS-EEND) |

## Repository

The official Pytorch implementation of "Frame-wise streaming end-to-end speaker diarization with non-autoregressive self-attention-based attractors". \[ICASSP 2024\] and "LS-EEND: long-form streaming end-to-end neural diarization with online attractor extraction". \[TASLP 2025\]

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.