Music can produce a positive effect in runners’ motivation and performance. Nevertheless, these effects vary depending on the user’s location, the emotions that she/he feels at each moment or the type of training session. In this paper, a context and emotion-aware system for the recommendation and playing of Spotify songs is presented. It consists in a location-based mobile application that interacts with a novel emotional wearable and a recommendation service that predicts the next song to be recommended. These predictions are performed by an intelligent system that combines artificial intelligent techniques with geodata and emotionally-annotated music. A wide variety of location-based services and music services available in Internet have been integrated into the recommender in order to support the decision-making process in a real environment. The final solution has been customized to be tested in the city of Zaragoza.

音乐可以对跑步者的动力和表现产生积极影响。但是，这些效果会根据用户的位置，她/他每时每刻的情绪或培训课程的类型而变化。在本文中，一个用于Spotify推荐和播放的上下文和情绪感知系统歌曲被呈现。它包含一个基于位置的移动应用程序，该应用程序与一种新颖的情感可穿戴设备进行交互，并具有一个推荐服务，该服务可预测要推荐的下一首歌曲。这些预测是通过将人工智能技术与地理数据和带有情感注释的音乐相结合的智能系统执行的。推荐器中已集成了Internet上可用的各种基于位置的服务和音乐服务，以支持实际环境中的决策过程。最终解决方案已经过定制，可以在萨拉戈萨市进行测试。