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CLASSIFYING SOUNDTRACKS WITH AUDIO TEXTURE …
https://www.ee.columbia.edu/~dpwe/pubs/EllisZM11-texture.pdf
with a range of features specifically aimed at sound textures. Section 2 describes the task and our data in more detail. Section 3 describes our approach, including the texture fea-ture set, the baseline MFCC features, and the SVM classifier. Section 4 reports our results on both feature sets and their combination. We draw conclusions in section 5. 2.
[PDF] Classifying soundtracks with audio texture features ...
https://www.semanticscholar.org/paper/Classifying-soundtracks-with-audio-texture-features-Ellis-Zeng/a41245407a93ec5ce6a7489fa03b0844dfefbfab
(PDF) Classifying soundtracks with audio texture features
https://www.researchgate.net/publication/224246555_Classifying_soundtracks_with_audio_texture_features
Classifying soundtracks with audio texture features | IEEE ...
https://ieeexplore.ieee.org/abstract/document/5947699/
Classifying Soundtracks with Audio Texture Features,” …
https://citeseerx.ist.psu.edu/showciting?cid=13811243
CiteSeerX — Classifying soundtracks with audio texture ...
https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.228.1408
Classifying soundtracks with audio texture features
https://www.infona.pl/resource/bwmeta1.element.ieee-art-000005947699
Sound textures may be defined as sounds whose character depends on statistical properties as much as the specific details of each individually-perceived event. Recent work has devised a set of statistics that, when synthetically imposed, allow listeners to identify a wide range of environmental sound textures. In this work, we investigate using these statistics for automatic …
Classifying soundtracks with audio texture features - CORE
https://core.ac.uk/display/161440882
Classifying soundtracks with audio texture features - CORE
https://core.ac.uk/display/205889597
Automatic Music Genre Classification Using Timbral Texture ...
https://icact.org/upload/2015/0053/20150053_finalpaper.pdf
components to be considered for better genre classification, which are audio feature extraction and classifier. This paper incorporates two different kinds of features for genre classification, timbral texture and rhythmic content features. Timbral texture contains the Mel-frequency Cepstral Coefficient (MFCC) with
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