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CORDIS

Artificial Intelligence for Lyrics Comprehension

Project description

Analysing song lyrics for personalised music streaming

Data science and machine learning are changing the music business. Algorithms based on artificial intelligence (AI) make it possible for music to be streamed based on user preferences. Currently, user-centric playlists hinges on recommendation systems consider the similarities between songs identified by their soundwaves. Classification is based on conventional song tags (author, genre, period, or in some cases, mood) and collaborative tagging by users. As such, the actual lyrics of the songs are not considered. This ERC-funded project LyrAIcs will develop an AI-based recommendation engine (web service API) for analysing song lyrics using POSTDATA project algorithms as its technical scaffold.

Objective

The age of machine learning and data analytics have changed the habits of entertainment. Recommendation systems have been improving in the last years, with relevant commercial purposes, and many top-level companies –such as Amazon, Google or Netflix- are investing high amounts of money in improving their algorithms based on Artificial Intelligence. The case of music has been especially relevant, as the market has drastically changed in the last 10 years, moving towards a user-centric streaming model, where user preferences make the difference and dynamic playlists are the key of streaming success. Recommenders are built based on three main strategies:
1) similarities between songs that are identified by their soundwaves;
2) classification using conventional tags for songs, such as author, genre, period or, in some cases, mood; and
3) collaborative tagging by users.
In this context, song lyrics (the text of songs) are barely considered for the improvement of these strategies. Moreover, recommendations based on lyrics are done by hand with uneven criteria and filters. This Proof of Concept proposes the creation of an AI based recommendation engine (i.e. web service API) for analyzing song lyrics using POSTDATA ERC Project algorithms as its technical scaffold. Natural Language Processing tools for poetry analysis will be used to build a web service API to process lyrics and extract knowledge as additional metadata to enrich the companies´recommender systems. This approach will open an exciting opportunity to contribute to boosting the music entertainment world using artificial intelligence and language technologies.

Host institution

IE UNIVERSIDAD
Net EU contribution
€ 150 000,00
Address
CALLE CARDENAL ZUNIGA 12
40003 Segovia
Spain

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Region
Centro (ES) Castilla y León Segovia
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data

Beneficiaries (1)