Update README.md

README.md

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----
-license: apache-2.0
----
+2---
+language:
+- en
+- zh
+- ml
+- ja
+- hi
+- ko
+- te
+- ta
+- pa
+- fr
+- bn
+- kn
+- ar
+- th
+- de
+- es
+pretty_name: MISP-M3SD
+license: apache-2.0
+task_categories:
+- audio-classification
+tags:
+- speaker-diarization
+- audio-visual
+- multimodal
+- multilingual
+- dataset
+- robust-speech-processing
+- in-the-wild
+---
+# MISP-M3SD
+
+
+## Dataset Summary
+
+**MISP-M3SD** is a large-scale **multimodal**, **multi-scenario**, and **multilingual** dataset for **robust speaker diarization**, constructed from in-the-wild online videos. It contains more than **770 hours** of synchronised audio-visual recordings, covering **14 scenarios** and **16 languages**.
+
+The dataset is designed to support the development of speaker diarization systems with stronger **cross-domain generalisation** under realistic conditions, including background noise, reverberation, overlapping speech, off-screen speech, motion blur, unstable speaker visibility, and camera switching.
+
+To enable scalable construction, MISP-M3SD is built through a largely automated pipeline, including:
+
+1. multilingual multi-scenario media acquisition,
+2. data cleaning and preprocessing, and
+3. cross-modal consistency-guided annotation with selective manual verification.
+
+
+## Access
+
+To use MISP-M3SD:
+
+1. Download [`audio.zip`](./audio.zip) together with all split files ([`audio.z01`](./audio.z01), [`audio.z02`](./audio.z02), [`audio.z03`](./audio.z03), [`audio.z04`](./audio.z04), [`audio.z05`](./audio.z05), [`audio.z06`](./audio.z06));
+2. Extract the audio archive to obtain the released WAV files;
+3. Use [`oracle.rttm`](./oracle.rttm) as the **final diarization annotation file**;
+4. Use `video_information.xlsx` to access metadata and retrieve the corresponding source videos when needed.
+
+Because of storage limitations, the videos are not distributed as a complete packaged archive.