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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence
- natural sciences computer and information sciences data science natural language processing
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-POC - Proof of Concept Grant
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2020-PoC
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
40003 Segovia
Spain
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