fixed initial descriptions and the statistics table

README.md

@@ -19,15 +19,15 @@ source_datasets:
 ---
   
 
-# Dataset  Card  for  AVS-Spot  Dataset
+# Dataset  Card  for  AVS-Spot  Benchmark
 
   
 
-This  dataset  is  associated  with  the  paper: "Understanding  Co-Speech  Gestures  in-the-wild"
+This dataset is associated with the paper: "Understanding Co-Speech Gestures in-the-wild"
 
 - 📝 ArXiv:
 
--  🌐 Project  page: https://www.robots.ox.ac.uk/~vgg/research/jegal
+-  🌐 Project page: https://www.robots.ox.ac.uk/~vgg/research/jegal
 
  <p align="center">
     <img src="assets/teaser.gif", width="450"/>
@@ -37,9 +37,9 @@ We present **JEGAL**, a **J**oint **E**mbedding space for **G**estures, **A**udi
 
 ## 📋 Table  of  Contents
 
-- [Dataset  Card  for  AVS-Spot  Dataset](#dataset-card-for-avs-spot-dataset)
+- [Dataset  Card  for  AVS-Spot  Benchmark?](#dataset-card-for-avs-spot-benchmark)
 - [📋 Table of Contents](#📋-table-of-contents)
-- [📚 Dataset Description](#📚-dataset-description)
+- [📚 What is the AVS-Spot Benchmark](#📚-dataset-description)
   - [Summary](#summary)
   - [Download instructions](#download-instructions)
 - [📝 Dataset Structure](#📝-dataset-structure)
@@ -54,15 +54,15 @@ We present **JEGAL**, a **J**oint **E**mbedding space for **G**estures, **A**udi
   
 
 
-## 📚 Dataset Description
+## 📚 What is the AVS-Spot Benchmark?
 
 ### Summary
 
-AVS-Spot is a **gestured word-spotting** video dataset containing **500 videos**, sampled from the AVSpeech official test dataset. The dataset is curated such that each video contains at least one clearly gestured word, annotated as the "target word". Additionally, we provide other annotations, including the text phrase, word boundaries, and speech-stress labels for each sample.
+AVS-Spot is a benchmark for evaluating the task of **gestured word-spotting**. It contains **500 videos**, sampled from the AVSpeech official test dataset. Each video contains at least one clearly gestured word, annotated as the "target word". Additionally, we provide other annotations, including the text phrase, word boundaries, and speech-stress labels for each sample.
 
-**Task:** Given an input video, a target word, and a transcript/speech, the goal is to localize the occurrence of the target word in the video based on gestures.
+**Task:** Given a target word, an input gesture video with a transcript/speech, the goal is to localize the occurrence of the target word in the video based on gestures.
 
-Some examples from the dataset are shown below. Note that the green box that highlights the word when it is gestured in the video is for visualization purposes only. The actual dataset does not contain these boxes; instead, we provide the target word's start and end frames as part of the annotations.
+Some examples from the dataset are shown below. Note: the green highlight box in the video is for visualization purposes only. The actual dataset does not contain these boxes; instead, we provide the target word's start and end frames as part of the annotations.
 
 <p align="center" style="display: flex; justify-content: center; flex-wrap: wrap;">
   <img src="assets/data1.gif" width="110" height="120" style="margin-right: 10px;"/>
@@ -170,9 +170,8 @@ Summarized dataset information is given below:
 ### Statistics
 
 | Dataset  | Split | # Hours | # Speakers | Avg. clip duration | # Videos |
-|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|
-AVS-Spot | test | 0.38 | 391 | 2.73 | 500 |
-
+|:--------:|:-----:|:-------:|:-----------:|:-----------------:|:--------:|
+| AVS-Spot | test  |  0.38   |     391     |        2.73       |   500    |
 
 Below, we show some additional statistics for the dataset: (i) Duration of videos in terms of number of frames, (ii) Wordcloud of most gestured words in the dataset, illustrating the diversity of the different words present, and (iii) The distribution of target-word occurences in the video.