mlsanityData to 14 Oct 2026

Anuvani-Diarization: Zero Shot Speaker Diarization and Annotation Conventions Across 22 Languages

arXiv 2610.20327 ↗First posted 14 Oct 2026cs.CLcited by 0

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Abstract (arXiv)

India's 22 scheduled languages are spoken by over a billion people in conversations that mix languages, often within one turn, overlap freely, and take place over telephones, in meetings, and in media. Knowing who spoke when, the task of speaker diarization, is essential to speech applications for such conversation: voice agents conversing with several people at once, speaker attributed transcription of meetings and calls, contact center analytics, and media monitoring. We present a systematic study of speaker diarization across all 22 languages on IndicDiarBench and introduce Anuvani-Diarization, which adapts a self-supervised end-to-end segmentation model to Indian conversation with uncertainty aware silver supervision. Evaluated zero shot alongside nine recent diarization systems, it reaches a duration weighted diarization error rate (DER) of 16.78% on all 1,164 recordings, the lowest of all systems we ran and second only to the best published result (16.0%), and leads the three strongest rivals in 14 of 22 languages. It matches its parent on six international benchmarks. We also show that the benchmark's utterance level annotation convention is a hidden variable worth 1.9 to 4.1 DER points, depending on the system, and that a convention learned from other Indian transcriptions does not transfer.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 28 of its 58 references that are in the map. First posted on arXiv 14 Oct 2026.

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References · 28

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  12. 2021AISHELL-4: An Open Source Dataset for Speech Enhancement, Separation, Recognition and Speaker Diarization in Conference Scenariocited by 60
16 more
  1. 2021Multilingual and code-switching ASR challenges for low resource Indian languagescited by 53
  2. 2020The Third DIHARD Diarization Challengecited by 49
  3. 2021Towards Building ASR Systems for the Next Billion Userscited by 47
  4. 2024IndicVoices: Towards building an Inclusive Multilingual Speech Dataset for Indian Languagescited by 41
  5. 2022Open Source MagicData-RAMC: A Rich Annotated Mandarin Conversational(RAMC) Speech Datasetcited by 40
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  7. 2020Integrating end-to-end neural and clustering-based diarization: Getting the best of both worldscited by 35
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  9. 2024Sortformer: A Novel Approach for Permutation-Resolved Speaker Supervision in Speech-to-Text Systemscited by 15
  10. 2023SPRING-INX: A Multilingual Indian Language Speech Corpus by SPRING Lab, IIT Madrascited by 11
  11. 2025Streaming Sortformer: Speaker Cache-Based Online Speaker Diarization with Arrival-Time Orderingcited by 8
  12. 2025Efficient and Robust Speaker Diarization via Structured Pruning of Self-Supervised Modelscited by 7
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  14. 2026Tight Boundary Prediction in Speaker Diarization Using Causal-Anticausal Consistencycited by 1
  15. 2026Indic DiarBench: A Multilingual Joint Diarization and ASR Benchmark for Indian Languagescited by 1
  16. 2026Diarization Error Decomposition Under Pause Annotation Ambiguitycited by 1

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