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Audio Classification Method Based on Machine Learning

https://doi.org/10.1109/icitbs.2016.98

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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An analysis of content-based classification of audio signals using a fuzzy c-means algorithm

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Importance of audio feature reduction in automatic music genre classification

inferredcites →https://doi.org/10.1007/s11063-014-9357-6openalex-snapshot

Soft Margin Based Low-Rank Audio Signal Classification

inferredcites →https://doi.org/10.1007/s11432-013-4821-xopenalex-snapshot

Tensor semantic model for an audio classification system

inferredcites →https://doi.org/10.1016/j.apacoust.2014.03.006openalex-snapshot

Classification of audio events using permutation transformation

inferredcites →https://doi.org/10.1016/j.dsp.2013.01.004openalex-snapshot

Dictionary learning based sparse coefficients for audio classification with max and average pooling

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Cross-covariance-based features for speech classification in film audio

inferredcites →https://doi.org/10.1109/taslp.2014.2359628openalex-snapshot

Mixed Stereo Audio Classification Using a Stereo-Input Mixed-to-Panned Level Feature

inferredcites →https://doi.org/10.1109/taslp.2014.2375575openalex-snapshot

Histogram of gradients of Time-Frequency Representations for Audio Scene Detection

inferredcites →https://doi.org/10.1145/2542182.2542197openalex-snapshot

Audio classification with low-rank matrix representation features

inferredcites →https://doi.org/10.1155/2015/209814openalex-snapshot

Optimized Audio Classification and Segmentation Algorithm by Using Ensemble Methods

inferredcites →https://doi.org/10.1186/s13636-016-0086-9openalex-snapshot

Semi-supervised feature selection for audio classification based on constraint compensated Laplacian score

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