File size: 4,351 Bytes
31e3a75 d3cfafa 31e3a75 bf4bede d3cfafa bf4bede d3cfafa bf4bede d3cfafa bf4bede d3cfafa bf4bede d3cfafa 31e3a75 bf4bede f37af87 9b16974 a6ed1f7 c5a40f8 a6ed1f7 31e3a75 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 |
---
language:
- en
- de
license: apache-2.0
task_categories:
- text-classification
- summarization
dataset_info:
- config_name: whisper_v1
features:
- name: segment_index
dtype: string
- name: start_time
dtype: float32
- name: end_time
dtype: float32
- name: transcribed_text
dtype: string
- name: game
dtype: string
splits:
- name: train
num_bytes: 110289348
num_examples: 780160
download_size: 34176839
dataset_size: 110289348
- config_name: whisper_v1_en
features:
- name: segment_index
dtype: int32
- name: start_time
dtype: float32
- name: end_time
dtype: float32
- name: transcribed_text
dtype: string
splits:
- name: train
num_bytes: 31843296
num_examples: 563064
download_size: 96617459
dataset_size: 31843296
- config_name: whisper_v2
features:
- name: segment_index
dtype: int32
- name: start_time
dtype: float32
- name: end_time
dtype: float32
- name: transcribed_text
dtype: string
splits:
- name: train
num_bytes: 47409793
num_examples: 761240
download_size: 96617459
dataset_size: 47409793
- config_name: whisper_v2_en
features:
- name: segment_index
dtype: string
- name: start_time
dtype: float32
- name: end_time
dtype: float32
- name: transcribed_text
dtype: string
splits:
- name: train
num_bytes: 32198972
num_examples: 538990
download_size: 96617459
dataset_size: 32198972
- config_name: whisper_v3
features:
- name: segment_index
dtype: string
- name: start_time
dtype: float32
- name: end_time
dtype: float32
- name: transcribed_text
dtype: string
splits:
- name: train
num_bytes: 52528392
num_examples: 923221
download_size: 96617459
dataset_size: 52528392
configs:
- config_name: whisper_v1
data_files:
- split: train
path: whisper_v1/train-*
default: true
---
# SoccerNet-Echoes
Official repo for the paper: [SoccerNet-Echoes: A Soccer Game Audio Commentary Dataset](https://arxiv.org/abs/2405.07354).
## Dataset
Each folder inside the **Dataset** directory is categorized by league, season, and game. Within these folders, JSON files contain the transcribed and translated game commentary.
```python
📂 Dataset
├── 📁 whisper_v1
│ ├── 🏆 england_epl
│ │ ├── 📅 2014-2015
│ │ │ └── ⚽ 2016-03-02 - 23-00 Liverpool 3 - 0 Manchester City
│ │ │ ├── ☁️ 1_asr.json
│ │ │ └── ☁️ 2_asr.json
│ │ ├── 📅 2015-2016
│ │ └── ...
│ ├── 🏆 europe_uefa-champions-league
│ └── ...
├── 📁 whisper_v1_en
│ └── ...
├── 📁 whisper_v2
│ └── ...
├── 📁 whisper_v2_en
│ └── ...
├── 📁 whisper_v3
│ └── ...
whisper_v1: Contains ASR from Whisper v1.
whisper_v1_en: English-translated datasets from Whisper v1.
whisper_v2: Contains ASR from Whisper v2.
whisper_v2_en: English-translated datasets from Whisper v2.
whisper_v3: Contains ASR from Whisper v3.
```
Each JSON file has the following format:
```python
{
"segments": {
segment index (int):[
start time in second (float),
end time in second (float),
transcribed text from ASR
]
....
}
}
```
The top-level object is named segments.
It contains an object where each key represents a unique segment index (e.g., "0", "1", "2", etc.).
Each segment index object has the following properties:
```python
start_time: A number representing the starting time of the segment in seconds.
end_time: A number representing the ending time of the segment in seconds.
text: A string containing the textual content of the commentary segment.
```
## Citation
Please cite our work if you use the SoccerNet-Echoes dataset:
<pre><code>
@misc{gautam2024soccernetechoes,
title={SoccerNet-Echoes: A Soccer Game Audio Commentary Dataset},
author={Sushant Gautam and Mehdi Houshmand Sarkhoosh and Jan Held and Cise Midoglu and Anthony Cioppa and Silvio Giancola and Vajira Thambawita and Michael A. Riegler and Pål Halvorsen and Mubarak Shah},
year={2024},
eprint={2405.07354},
archivePrefix={arXiv},
primaryClass={cs.SD},
doi={10.48550/arXiv.2405.07354}
}
</code></pre> |