Mercurial > hg > rhythm-melody-feature-evaluation

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+Scripts to assess invariance of rhythmic and melodic descriptors as described in [1]. This code extracts rhythmic and melodic audio features for a dataset of synthesised rhythms and melodies. It assesses the invariance of the features to transformations of the timbre, recording quality, tempo and pitch via a classification and retrieval experiment.
+You can download the dataset of synthesised rhythms and melodies from [2].
+If you use this software or dataset for research please cite [1].
+
+For any questions please contact m.x.panteli{at}gmail.com.
+This code is licensed under the terms of the MIT License.
+Copyright (c) 2016 Maria Panteli.
+
+Usage:
+1) extract_features.py: Extracts the scale transform rhythmic descriptor and pitch bihistogram melodic descriptor for audio recordings located in audio/rhythms and audio/melodies. Requires the dataset to be downloaded in directory ‘audio’.
+
+2) evaluate.py: Assesses the performance of each descriptor with respect to the different transformations and transformation values by a classification and retrieval experiment. The classification experiment runs a 5-fold cross-validation on the dataset with 30 rhythm/melody classes and 100 instances each. The retrieval experiment queries one instance from each rhythm/melody class and assesses the recall rate in the top 99 positions.
+
+3) results.py: Prints results from the classification and retrieval experiments to Latex tables and assesses the effect of music style and monophonic versus polyphonic character via box plots and paired t-tests.
+
+
+[1] M. Panteli and S. Dixon. On the Evaluation of Rhythmic and Melodic Descriptors for Music Similarity. In Proceedings of the 17th International Society for Music Information Retrieval Conference, pages 468-474, 2016.
+
+[2] Rhythms - https://archive.org/details/panteli_maria_rhythm_dataset
+     Melodies - https://archive.org/details/panteli_maria_melody_dataset
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-
-\f0\fs24 \cf0 Scripts to assess invariance of rhythmic and melodic descriptors as described in [1]. This code extracts rhythmic and melodic audio features for a dataset of synthesised rhythms and melodies. It assesses the invariance of the features to transformations of the timbre, recording quality, tempo and pitch via a classification and retrieval experiment. \
-You can download the dataset of synthesised rhythms and melodies from [2]. \
-If you use this software or dataset for research please cite [1]. \
-\
-For any questions please contact m.x.panteli\{at\}gmail.com.\
-This code is licensed under the terms of the MIT License. \
-Copyright (c) 2016 Maria Panteli.\
-\
-Usage: \
-1) extract_features.py: Extracts the scale transform rhythmic descriptor and pitch bihistogram melodic descriptor for audio recordings located in audio/rhythms and audio/melodies. Requires the dataset to be downloaded in directory \'91audio\'92.\
-\
-2) evaluate.py: Assesses the performance of each descriptor with respect to the different transformations and transformation values by a classification and retrieval experiment. The classification experiment runs a 5-fold cross-validation on the dataset with 30 rhythm/melody classes and 100 instances each. The retrieval experiment queries one instance from each rhythm/melody class and assesses the recall rate in the top 99 positions. \
-\
-3) results.py: Prints results from the classification and retrieval experiments to Latex tables and assesses the effect of music style and monophonic versus polyphonic character via box plots and paired t-tests. \
-\
-\
-[1] M. Panteli and S. Dixon. On the Evaluation of Rhythmic and Melodic Descriptors for Music Similarity. In
-\i Proceedings of the 17th International Society for Music Information Retrieval Conference
-\i0 , pages 468-474, 2016.\
-\
-[2] Rhythms - {\field{\*\fldinst{HYPERLINK "https://archive.org/details/panteli_maria_hotmail_rhythm"}}{\fldrslt https://archive.org/details/panteli_maria_rhythm_dataset}}  \
-     Melodies - {\field{\*\fldinst{HYPERLINK "https://archive.org/details/panteli_maria_hotmail_melody"}}{\fldrslt https://archive.org/details/panteli_maria_melody_dataset}}}
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