Update README.md

README.md

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-license: cc-by-4.0
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+---
+license: cc-by-4.0
+task_categories:
+- zero-shot-classification
+language:
+- en
+size_categories:
+- 10K<n<100K
+---
+# Can Large Language Models Help Multimodal Language Analysis? MMLA: A Comprehensive Benchmark
+
+MMLA is the first comprehensive multimodal language analysis benchmark for evaluating foundation models. It has the following features:
+
+- **Large** Scale: 61K+ multimodal samples.
+- **Various** Sources: 9 datasets.
+- **Three** Modalities: text, video, and audio
+- Both **Acting** and **Real-world** Scenarios: films, TV series, YouTube, Vimeo, Bilibili, TED, improvised scripts, etc.
+- **Six** Core Dimensions in Multimodal Language Analysis: intent, emotion, sentiment, dialogue act, speaking style, and communication behavior.
+