README.md

---
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>