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.

在足球领域，应用自动语音识别（ASR）技术提供了许多运动分析的机会，本研究介绍了 SoccerNet-Echoes 数据集，利用 ASR 自动生成足球比赛音频解说的文字转录，通过丰富的文字信息增强视频内容，扩展了 SoccerNet 数据集的用途，包括提升的动作定位、自动字幕生成和比赛摘要等多样化的应用领域，通过结合视觉、听觉和文字信息，SoccerNet-Echoes 旨在为捕捉足球比赛动态特征的算法开发提供全面的资源，并且强调多模态方法在运动分析中的意义，以及丰富的数据集对于推动该领域的研究和发展所带来的影响。