CS229 Project: Music Search Engine
نویسنده
چکیده
With the abundance of digital music files on the internet, how to efficiently and effectively find a music piece is crucial. Conventional music search systems utilize text information of the music, such as the title of a song, a singer’s name, or the lyrics of a song. In many cases, such text-based music search tool is not sufficient. Often, a user may remember how to sing part of a song he/she has once heard, and wants to find the complete piece of music on the internet, but not knowing any other information about the music (i.e. tile, composer name), the search can not be done with conventional search tools. Such scenario demands the use of a query-by-humming (QBH) music search system.
منابع مشابه
CS229 Project Report Offline Music Recommendation
The goal of this project was to recommend songs to users based solely on their listening histories, with no information about the music. We applied various Collaborative Filtering methods to achieve this: user-user neighborhood models, item-item neighborhood models and latent factor models. We achieved the best results with item-item cosine similarity. The code for this project can be found here.
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The C-BRAHMS project develops computational methods for content-based retrieval and analysis of music data. A summary of the recent algorithmic and experimental developments of the project is given. The search engine developed by the project is available at http://www.cs.helsinki.fi/group/cbrahms.
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