Instrument identification in polyphonic music signals based on individual partials
Jayme Garcia Arnal Barbedo,George Tzanetakis +1 more
- pp 401-404
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TLDR
A new approach to instrument identification based on individual partials is presented, which makes identification possible even when the concurrently played instrument sounds have a high degree of spectral overlapping.Abstract:
A new approach to instrument identification based on individual partials is presented. It makes identification possible even when the concurrently played instrument sounds have a high degree of spectral overlapping. A pairwise comparison scheme which emphasizes the specific differences between each pair of instruments is used for classification. Finally, the proposed method only requires a single note from each instrument to perform the classification. If more than one partial is available the resulting multiple classification decisions can be summarized to further improve instrument identification for the whole signal. Encouraging classification results have been obtained in the identification of four instruments (saxophone, piano, violin and guitar).read more
Citations
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Classifying musical instruments using speech signal processing methods
TL;DR: Among the features used, after MFCC, ZCR proved to be the optimal feature for the classification of drum instrument, and the most significant feature for classifying Guitar, Violin and Drum is MFCC as it gives the better accurate results.
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Overlapped soundtracks segmentation using singular spectrum analysis and random forests
Duraid Y. Mohammed,Francis F. Li +1 more
TL;DR: The classification performance of overlapped soundtracks is effectively improved and singular spectrum analysis has been found to be an efficient way to discriminate speech/music in mixed soundtracks.
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A Multiple-Expert Framework for Instrument Recognition
TL;DR: A new approach towards feature-based instrument recognition is presented that makes use of redundancies in the harmonic structure and temporal development of a note that is targeted at transferability towards use on polyphonic material.
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Stratification of String Instruments Using Chroma-Based Features
TL;DR: The proposed work relies on Chroma-based low-dimensional feature vector to categorize String instruments, which is an octave independent estimation of strength of all possible notes in Western 12 note scale at different points of time.
References
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Journal ArticleDOI
Empirical Methods to Determine the Number of Sources in Single-Channel Musical Signals
TL;DR: A carefully tuned and tested two-stage system that is able to function effectively even in extremely underdetermined conditions is developed, using both random and harmonically related mixtures of one to six sources taken from two widely available musical instrument databases.
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Automatic Musical Genre Classification Using a Flexible Approach
TL;DR: A flexible method to classify musical audio signals automatically into musical genres is introduced, which makes it possible to treat adequately the huge amount of songs influenced by or resulting from the fusion of two or more musical genres.