Update task categories to `video-text-to-text`

This PR updates the `task_categories` metadata field to `video-text-to-text`. This change more accurately reflects the dataset's purpose as described in the paper abstract, which involves understanding "gesture-speech-text associations" using a "tri-modal video-gesture-speech-text representation". The existing categories `feature-extraction` and `text-to-video` are replaced as they do not fully capture the multimodal understanding nature of the dataset's primary tasks like gesture word spotting and cross-modal retrieval.

README.md

@@ -8,8 +8,7 @@ size_categories:
 source_datasets:
 - extended
 task_categories:
-- feature-extraction
-- text-to-video
+- video-text-to-text
 pretty_name: AVS-Spot
 tags:
 - co-speech gestures
@@ -18,7 +17,7 @@ tags:
 - multimodal-learning
 ---
 
-# Dataset  Card  for  AVS-Spot  Benchmark
+# Dataset Card for AVS-Spot Benchmark
 
 
 This dataset is associated with the paper: "Understanding Co-Speech Gestures in-the-wild"
@@ -33,9 +32,9 @@ This dataset is associated with the paper: "Understanding Co-Speech Gestures in-
   
 We present **JEGAL**, a **J**oint **E**mbedding space for **G**estures, **A**udio and **L**anguage. Our semantic gesture representations can be used to perform multiple downstream tasks such as cross-modal retrieval, spotting gestured words, and identifying who is speaking solely using gestures.  
 
-## 📋 Table  of  Contents
+## 📋 Table of Contents
 
-- [Dataset  Card  for  AVS-Spot  Benchmark](#dataset-card-for-avs-spot-benchmark)
+- [Dataset Card for AVS-Spot Benchmark](#dataset-card-for-avs-spot-benchmark)
 - [📋 Table of Contents](#📋-table-of-contents)
 - [📚 What is the AVS-Spot Benchmark?](#📚-what-is-the-AVS-Spot-Benchmark?)
   - [Summary](#summary)
@@ -50,7 +49,6 @@ We present **JEGAL**, a **J**oint **E**mbedding space for **G**estures, **A**udi
   
 
 
-
 ## 📚 What is the AVS-Spot Benchmark?
 
 ### Summary