Searching for authors named "Thomas Lidy" – sorted by Relevance.
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Genre-oriented Organization of Music Collections using the SOMeJB System: An Analysis of Rhythm Patterns and Other Features
- With the advent of larger electronic music repositories, the automatic organization of music into different genre categories is receiving increased attention. The creation of such genre hierarchies, as well as ways for providing useful interfaces to these, poses an interesting challenge. With the SO
- Cited by 1 (0 self) – Add To MetaCart
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2005, ‘MIREX 2005:Combined Fluctuation Features for Music Genre Classification’. Extended Abstract. MIREX genre classification contest (www.music-ir.org/evaluation/mirex-results
- CLASSIFICATION We submitted a system that uses combinations of three feature sets (Rhythm Patterns, Statistical Spectrum Descriptor and Rhythm Histogram) to the MIREX 2005 audio genre classification task. All feature sets are based on fluctuation of modulation amplitudes in psychoacoustically transf
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IMPROVING GENRE CLASSIFICATION BY COMBINATION OF AUDIO AND SYMBOLIC DESCRIPTORS USING A TRANSCRIPTION SYSTEM
- Recent research in music genre classification hints at a glass ceiling being reached using timbral audio features. To overcome this, the combination of multiple different feature sets bearing diverse characteristics is needed. We propose a new approach to extend the scope of the features: We transcr
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Evaluation of Feature Extractors and Psycho-Acoustic Transformations for Music Genre Classification
- We present a study on the importance of psycho-acoustic transformations for effective audio feature calculation. From the results, both crucial and problematic parts of the algorithm for Rhythm Patterns feature extraction are identified. We furthermore introduce two new feature representations in th
- Cited by 26 (12 self) – Add To MetaCart
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Decision Manifolds: Classification Inspired by Self-Organization
- Abstract — We present a classifier algorithm that approximates the decision surface of labeled data by a patchwork of separating hyperplanes. The hyperplanes are arranged in a way inspired by how Self-Organizing Maps are trained. We take advantage of the fact that the boundaries can often be approxi
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Automatic Audio Segmentation: Segment Boundary and Structure Detection in Popular Music
- Abstract. Automatic Audio Segmentation aims at extracting information on a song’s structure, i.e., segment boundaries, musical form and semantic labels like verse, chorus, bridge etc. This information can be used to create representative song excerpts or summaries, to facilitate browsing in large mu
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Map-Based Music Interfaces for Mobile Devices
- The pervasion of digital music calls for novel techniques to search, retrieve and access music collections. Particularly mobile devices are, due to their limited display size and input capabilities, in a need of possibilities for intuitive and quick selection of music that go beyond mere browsing th
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Sound Re-Synthesis From Rhythm Pattern Features - Audible Insight into a Music Feature Extraction Process
- For tasks like musical genre identification and similarity searches in audio databases, audio files have to be described by suitable feature sets. Since these feature sets usually try to capture diverse discriminative characteristics, it is interesting and desirable to create an acoustic representat
- Cited by 8 (3 self) – Add To MetaCart
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Content-based organization of digital audio collections
- With increasing amounts of audio being stored and distributed electronically, intuitive and efficient access to large music collections is becoming crucial. To this end we are developing algorithms for audio feature extraction, allowing to compute acoustic similarity between pieces of music, as well
- Cited by 5 (3 self) – Add To MetaCart
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The Map of Mozart
- We present a study on using a Mnemonic Self-Organizing Map for clustering a very homogeneous collection of music. In particular, we create a map containing the complete works of Wolfgang Amadeus Mozart. We study and analyze the clustering capabilities of the SOM on this very focused collection. We f
- Cited by 4 (2 self) – Add To MetaCart

