Automatic Recognition of Samples in Musical Audio
Jan Van Balen · Zenodo (CERN European Organization for Nuclear Research) · 2011
Sampling can be described as the reuse of a fragment of another artist’s recording in a new musical work. This project aims at developing an algorithm that, given a database of candidate recordings, can detect samples of these in a given query. The problem of sample identification as a music information retrieval task has not been addressed before, it is therefore first defined and situated in the broader context of sampling as a musical phenomenon. The most relevant research to date is brought together and critically reviewed in terms of the requirements that a sample recognition system must meet. The assembly of a ground truth database for evaluation was also part of the work and restricted to hip hop songs, the first and most famous genre to be built on samples. Techniques from audio fingerprinting, remix recognition and cover detection, amongst other research, were used to build a number of systems investigating different strategies for sample recognition. The systems were evaluated using the ground truth database and their performance is discussed in terms of the retrieved items to identify the main challenges for future work. The results are promising, given the novelty of the task.