Title :
How similar do songs sound? Towards modeling human perception of musical similarity
Author :
Herre, Jürgen ; Allamanche, Eric ; Ertel, Chris
Author_Institution :
Fraunhofer Inst. for Integrated Circuits FhG-IIS, Erlangen, Germany
Abstract :
Human listeners have a well-developed feeling for identifying "whether two songs sound similar" or whether they do not. Even though this type of judgment usually also involves a considerable amount of the listener\´s background knowledge, it has been demonstrated that an algorithmic model of this type of similarity can be achieved by merely evaluating the signal\´s low-level acoustic features. The paper describes a system for assessing subjectively sound similarity between pairs of musical items by using a number of such signal features. The system\´s performance is assessed by means of a subjective listening test that is based on a modification of a test methodology originally standardized for subjective sound quality evaluation. A number of interesting applications for such a technology are described.
Keywords :
acoustic signal processing; audio signal processing; feature extraction; hearing; music; feature extraction; human perception; low-level acoustic features; musical similarity; signal features; song similarity; subjective listening test; subjective sound similarity assessment; Acoustic measurements; Acoustic testing; Algorithm design and analysis; Cepstral analysis; Emulation; Feature extraction; Humans; Integrated circuit modeling; Signal processing algorithms; System testing;
Conference_Titel :
Applications of Signal Processing to Audio and Acoustics, 2003 IEEE Workshop on.
Print_ISBN :
0-7803-7850-4
DOI :
10.1109/ASPAA.2003.1285825