Natural Language Processing (NLP) is one of the most popular fields of Artificial Intelligence and its applications are diverse. This article presents a recommender system, through a web application, that extracts the lyrics of a song entered in audio format and uses NLP techniques to process the textual corpus of the lyrics and recommend a title for the song. The level of effectiveness of the system was analyzed, measuring the percentage of similarity between the ground truth, which is the original title of the song, and our recommendation. For the experiments, a dataset of 30 songs was used divided into three taxonomies, small, medium, and large, that change according to the length of tokens of the original title. The results show an accuracy of 70% for small titles and 20% for medium and long titles. It is also shown that the web tool is enabled to formulate control of lexical content in songs since it does not use the original title of the song as input.