Music Room - A Chatbot Based Song Recommender using Sentiment Analysis

Abstract

In this era of technological advancement, mood-based music recommendations are highly needed because they help people relieve stress and listen to mood-sensitive music. In our project, system recommends music based on the user's mood in communication(chatting) with chatbots. The motive of this our project is to identify the user’s emotion. Once the mood is identified, the API will play the song, depending on what the user has selected and the current mood. The system we propose can be run on the user's desktop and is implemented as an application whose main purpose is to reliably determine the user's mood. But is it more important not to worry about weird chatbots that exist all over the world and are created primarily for business purposes? This project is building a complete chatbot service to visit. And blame chatbots for not being business-oriented. It will be a casual conversation. In addition, chatbot recommends list of songs to users that based on their current tone. The recommended feature of this song uses basically the same Last.fm API as the popular Spotify API. It also uses the IBM Tone Analyzer API for conversation tone / sentiment analysis. It is very important to work with these types of APIs, as the preferred chatbots in the world today are data-driven conversations. Add user-oriented features. The reason Python needs to build chatbots is that Python is honestly chosen for open source chatbot libraries such as Scikit-learn and TensorFlow. Great for small datasets and simpler analyses. In addition, Python libraries tend to be more useful in creating such self-learning Architecture.