# SoccerNet-Echoes: A Soccer Game Audio Commentary Dataset

arXiv: https://arxiv.org/abs/2405.07354 · HTML: https://mlsanity.com/paper/2405.07354/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 40 references that are in the map.
- First posted on arXiv 12 May 2024.

## Builds on (most cited first, 22 of 22)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [BERTScore: Evaluating Text Generation with BERT](https://mlsanity.com/paper/1904.09675/) (2019)
- [VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training](https://mlsanity.com/paper/2203.12602/) (2022)
- [Dense-Captioning Events in Videos](https://mlsanity.com/paper/1705.00754/) (2017)
- [SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos](https://mlsanity.com/paper/1804.04527/) (2018)
- [Recent Advances in End-to-End Automatic Speech Recognition](https://mlsanity.com/paper/2111.01690/) (2021)
- [SoccerNet-v2: A Dataset and Benchmarks for Holistic Understanding of Broadcast Soccer Videos](https://mlsanity.com/paper/2011.13367/) (2020)
- [End-to-end Generative Pretraining for Multimodal Video Captioning](https://mlsanity.com/paper/2201.08264/) (2022)
- [Multi-modal Dense Video Captioning](https://mlsanity.com/paper/2003.07758/) (2020)
- [MAD: A Scalable Dataset for Language Grounding in Videos from Movie Audio Descriptions](https://mlsanity.com/paper/2112.00431/) (2021)
- [SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos](https://mlsanity.com/paper/2204.06918/) (2022)
- [SoccerNet-Caption: Dense Video Captioning for Soccer Broadcasts Commentaries](https://mlsanity.com/paper/2304.04565/) (2023)
- [VARS: Video Assistant Referee System for Automated Soccer Decision Making from Multiple Views](https://mlsanity.com/paper/2304.04617/) (2023)
- [SoccerNet Game State Reconstruction: End-to-End Athlete Tracking and Identification on a Minimap](https://mlsanity.com/paper/2404.11335/) (2024)
- [Deep Learning for Environmentally Robust Speech Recognition: An Overview of Recent Developments](https://mlsanity.com/paper/1705.10874/) (2017)
- [GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation](https://mlsanity.com/paper/2303.14655/) (2023)
- [A Survey on Content-Aware Video Analysis for Sports](https://mlsanity.com/paper/1703.01170/) (2017)
- [X-VARS: Introducing Explainability in Football Refereeing with Multi-Modal Large Language Model](https://mlsanity.com/paper/2404.06332/) (2024)
- [Improved Soccer Action Spotting using both Audio and Video Streams](https://mlsanity.com/paper/2011.04258/) (2020)
- [SoccerNet 2023 Challenges Results](https://mlsanity.com/paper/2309.06006/) (2023)
- [A Case Study on Combining ASR and Visual Features for Generating Instructional Video Captions](https://mlsanity.com/paper/1910.02930/) (2019)
- [Whisper: Fast Flooding for Low-Power Wireless Networks](https://mlsanity.com/paper/1809.03699/) (2018)

## Built on by (most cited first, 12 of 12)

- [MatchTime: Towards Automatic Soccer Game Commentary Generation](https://mlsanity.com/paper/2406.18530/) (2024)
- [Towards Universal Soccer Video Understanding](https://mlsanity.com/paper/2412.01820/) (2024)
- [Towards AI-Powered Video Assistant Referee System (VARS) for Association Football](https://mlsanity.com/paper/2407.12483/) (2024)
- [SoccerChat: Integrating Multimodal Data for Enhanced Soccer Game Understanding](https://mlsanity.com/paper/2505.16630/) (2025)
- [Domain Adaptation of VLM for Soccer Video Understanding](https://mlsanity.com/paper/2505.13860/) (2025)
- [From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary](https://mlsanity.com/paper/2506.17294/) (2025)
- [Pixels or Positions? Benchmarking Modalities in Group Activity Recognition](https://mlsanity.com/paper/2511.12606/) (2025)
- [Do We Need Large VLMs for Spotting Soccer Actions?](https://mlsanity.com/paper/2506.17144/) (2025)
- [TennisExpert: Towards Expert-Level Analytical Sports Video Understanding](https://mlsanity.com/paper/2603.13397/) (2026)
- [Towards Automatic Soccer Commentary Generation with Knowledge-Enhanced Visual Reasoning](https://mlsanity.com/paper/2604.00057/) (2026)
- [Towards Athlete Fatigue Assessment from Association Football Videos](https://mlsanity.com/paper/2604.05636/) (2026)
- [SoccerNet 2026 Challenges Results](https://mlsanity.com/paper/2607.07320/) (2026)

## Abstract (arXiv)

The application of Automatic Speech Recognition (ASR) technology in soccer offers numerous opportunities for sports analytics. Specifically, extracting audio commentaries with ASR provides valuable insights into the events of the game, and opens the door to several downstream applications such as automatic highlight generation. This paper presents SoccerNet-Echoes, an augmentation of the SoccerNet dataset with automatically generated transcriptions of audio commentaries from soccer game broadcasts, enhancing video content with rich layers of textual information derived from the game audio using ASR. These textual commentaries, generated using the Whisper model and translated with Google Translate, extend the usefulness of the SoccerNet dataset in diverse applications such as enhanced action spotting, automatic caption generation, and game summarization. By incorporating textual data alongside visual and auditory content, SoccerNet-Echoes aims to serve as a comprehensive resource for the development of algorithms specialized in capturing the dynamics of soccer games. We detail the methods involved in the curation of this dataset and the integration of ASR. We also highlight the implications of a multimodal approach in sports analytics, and how the enriched dataset can support diverse applications, thus broadening the scope of research and development in the field of sports analytics.