Feature Selection for Dynamic Range Compressor Parameter Estimation

date-added: 2018-05-07 00:06:23 +0000 date-modified: 2018-05-07 00:09:42 +0000 keywords: feature selection,. intelligent music production, AES, intelligent audio effects local-url: sheng2018aes.pdf

[1]  Jacob Benesty,et al.  Pearson Correlation Coefficient , 2009 .

[2]  György Fazekas,et al.  SAFE: A System for the Extraction and Retrieval of Semantic Audio Descriptors , 2014 .

[3]  Joshua D. Reiss,et al.  Digital Dynamic Range Compressor Design—A Tutorial and Analysis , 2012 .

[4]  Nur Izura Udzir,et al.  A Study on Feature Selection and Classification Techniques for Automatic Genre Classification of Traditional Malay Music , 2008, ISMIR.

[5]  Jörn Loviscach,et al.  Music Icons: Procedural Glyphs for Audio Files , 2006, 2006 19th Brazilian Symposium on Computer Graphics and Image Processing.

[6]  James Bailey,et al.  Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance , 2010, J. Mach. Learn. Res..

[7]  Joshua D. Reiss,et al.  Semantic Description of Timbral Transformations in Music Production , 2016, ACM Multimedia.

[8]  György Fazekas,et al.  Automatic Control of the Dynamic Range Compressor Using a Regression Model and a Reference Sound , 2016 .

[9]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[10]  Tuomas Virtanen,et al.  Deep Neural Networks for Dynamic Range Compression in Mastering Applications , 2016 .

[11]  Rossitza Setchi,et al.  Feature selection using Joint Mutual Information Maximisation , 2015, Expert Syst. Appl..

[12]  Huan Liu,et al.  Toward integrating feature selection algorithms for classification and clustering , 2005, IEEE Transactions on Knowledge and Data Engineering.

[13]  Jane Labadin,et al.  Feature selection based on mutual information , 2015, 2015 9th International Conference on IT in Asia (CITA).

[14]  Masataka Goto,et al.  RWC Music Database: Music genre database and musical instrument sound database , 2003, ISMIR.

[15]  Joshua D. Reiss,et al.  Stem audio mixing as a content-basec transformation of audio features , 2017, 2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP).

[16]  Jean-Michel Poggi,et al.  Variable selection using random forests , 2010, Pattern Recognit. Lett..

[17]  György Fazekas,et al.  Selection of Audio Features for Music Emotion Recognition Using Production Music , 2014, Semantic Audio.

[18]  Joshua D. Reiss,et al.  Ten Years of Automatic Mixing , 2017 .

[19]  Joshua D. Reiss,et al.  Automatic subgrouping of multitrack audio , 2015 .

[20]  Di Sheng,et al.  Feature Design Using Audio Decomposition for Intelligent Control of the Dynamic Range Compressor , 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[21]  Wentian Li.  Mutual information functions versus correlation functions , 1990 .

[22]  Joshua D. Reiss,et al.  Intelligent Multitrack Dynamic Range Compression , 2015 .

[23]  Udo Zölzer,et al.  Adaptive digital audio effects (a-DAFx): a new class of sound transformations , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[24]  Joshua D. Reiss,et al.  Adaptive Audio Reproduction Using Personalized Compression , 2015 .

[25]  Bryan Pardo,et al.  Social-EQ: Crowdsourcing an Equalization Descriptor Map , 2013, ISMIR.