Musical instrument recognition using cepstral coefficients and temporal features

Author

Eronen, Antti ; Klapuri, Anssi

Author_Institution

Signal Process. Lab., Tampere Univ. of Technol., Finland

Volume

2

fYear

2000

fDate

2000

Abstract

In this paper, a system for pitch independent musical instrument recognition is presented. A wide set of features covering both spectral and temporal properties of sounds was investigated, and their extraction algorithms were designed. The usefulness of the features was validated using test data that consisted of 1498 samples covering the full pitch ranges of 30 orchestral instruments from the string, brass and woodwind families, played with different techniques. The correct instrument family was recognized with 94% accuracy and individual instruments in 80% of cases. These results are compared to those reported in other work. Also, utilization of a hierarchical classification framework is considered

Keywords

acoustic signal processing; cepstral analysis; feature extraction; musical instruments; pattern classification; brass family; cepstral coefficients; extraction algorithms; hierarchical classification framework; musical instrument recognition; orchestral instrument; pitch independent musical instrument recognition; spectral properties; string family; temporal features; temporal properties; woodwind family; Algorithm design and analysis; Cepstral analysis; Data mining; Instruments; Laboratories; Multiple signal classification; Music; Signal analysis; Signal processing algorithms; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on

Conference_Location

Istanbul

ISSN

1520-6149

Print_ISBN

0-7803-6293-4

Type

conf

DOI

10.1109/ICASSP.2000.859069

Filename

859069