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Musical genre classification of audio signals
TLDR
The automatic classification of audio signals into an hierarchy of musical genres is explored and three feature sets for representing timbral texture, rhythmic content and pitch content are proposed.
An experimental comparison of audio tempo induction algorithms
TLDR
One conclusion is that robust tempo induction entails the processing of frame features rather than that of onset lists, and a new "redundant" approach to tempo induction is proposed, inspired by knowledge of human perceptual mechanisms.
MARSYAS: a framework for audio analysis
TLDR
This paper describes MARSYAS, a framework for experimenting, evaluating and integrating techniques for audio content analysis in restricted domains and a new method for temporal segmentation based on audio texture that is combined with audio analysis techniques and used for hierarchical browsing, classification and annotation of audio files.
Automatic Musical Genre Classification of Audio Signals
TLDR
Algorithms for the automatic genre categorization of audio signals are described and a set of features for representing texture and instrumentation and a novel set of Features for representing rhythmic structure and strength are proposed.
Manipulation, analysis and retrieval systems for audio signals
TLDR
A general multi-feature audio texture segmentation methodology, feature extraction from mp3 compressed data, automatic beat detection and analysis based on the Discrete Wavelet Transform and musical genre classification combining timbral, rhythmic and harmonic features are described.
Polyphonic audio matching and alignment for music retrieval
We describe a method that aligns polyphonic audio recordings of music to symbolic score information in standard MIDI files without the difficult process of polyphonic transcription. By using this
Audio Analysis using the Discrete Wavelet Transform
TLDR
Automatic classification of various types of audio using the DWT is described and compared with other traditional feature extractors proposed in the literature.
Streamlined Tempo Estimation Based on Autocorrelation and Cross-correlation With Pulses
TLDR
A streamlined tempo estimation method that distills ideas from previous work by reducing the number of steps, parameters, and modeling assumptions while retaining good accuracy for music with a constant or near-constant tempo is presented.
Pitch Histograms in Audio and Symbolic Music Information Retrieval
TLDR
P Pitch Histograms are defined and proposed as a way to represent the pitch content of music signals both in symbolic and audio form and evaluated in the context of automatic musical genre classification.
Factors in automatic musical genre classification of audio signals
TLDR
This paper provides a detailed comparative analysis of various factors affecting automatic classification performance, such as choice of features and classifiers, using identical data collections and features.
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