Journal Forum

Synthetic Reverberator - January 1960
1 comment

Multichannel Sound Reproduction Quality Improves with Angular Separation of Direct and Reflected Sounds - June 2015
1 comment

Clean Audio for TV broadcast: An Object-Based Approach for Hearing-Impaired Viewers - April 2015

Access Journal Forum

AES E-Library

Automatic Extraction of Music Descriptors from Acoustic Signals Using EDS

Document Thumbnail

High-Level music descriptors are key ingredients for music information retrieval systems. Although there is a long tradition in extracting information from acoustic signals, the field of music information extraction is largely heuristic in nature. We present here a heuristic-based generic approach for extracting automatically high-level music descriptors from acoustic signals. This approach is based on Genetic Programming, used to build relevant features as functions of mathematical and signal processing operators. The search of relevant features is guided by specialized heuristics that embody knowledge about the signal processing functions built by the system. Signal processing patterns are used in order to control the general processing methods. In addition, rewriting rules are introduced to simplify overly complex expressions, and a caching system further reduces the computing cost of each cycle.

AES Convention: Paper Number:
Publication Date:

Click to purchase paper or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $20 for non-members, $5 for AES members and is free for E-Library subscribers.

Learn more about the AES E-Library

E-Library Location:

Start a discussion about this paper!

Facebook   Twitter   LinkedIn   Google+   YouTube   RSS News Feeds  
AES - Audio Engineering Society