High accuracy and octave error immune pitch detection algorithms
M. Dziubiński, Bożena Kostek
Abstract
M. Dziubiński, Bożena Kostek
Abstract
The aim of this paper is to present a method improving pitch estimation accuracy, showing high performance for both synthetic harmonic signals and musical instrument sounds. This method employs an Artificial Neural Network of a feed-forward type. In addition, octave error optimized pitch detection algorithm, based on spectral analysis is introduced. The proposed algorithm is very effective for signals with strong harmonic, as well as nearly sinusoidal contents. Experiments were performed on a variety of musical instrument sounds and sample results exemplifying main issues of both engineered algorithms are shown. 1.
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The aim of this paper is to present a method improving pitch estimation accuracy, showing high performance for both synthetic harmonic signals and musical instrument sounds. This method employs an Artificial Neural Network of a feed-forward type. In addition, octave error optimized pitch detection algorithm, based on spectral analysis is introduced. The proposed algorithm is very effective for signals with strong harmonic, as well as nearly sinusoidal contents. Experiments were performed on a variety of musical instrument sounds and sample results exemplifying main issues of both engineered algorithms are shown. 1.
Key concepts: Octave (electronics), Pitch detection algorithm, Computer science, Harmonic, Pitch (Music), Algorithm, Speech recognition, Musical instrument