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3 results for “edm music”
WaivOps EDM-HSE: Open Audio Resources for Machine Learning in Music
<p><strong>EDM-HSE Dataset</strong></p> <p>EDM-HSE is an open audio dataset containing a collection of code-generated drum recordings in the style of modern electronic house music. It includes 8,000 audio loops recorded in uncompressed stereo WAV format, created using custom audio samples and a MIDI drum dataset. The dataset also comes with paired JSON files containing MIDI note numbers (pitch) and tempo data, intended for supervised training of generative AI audio models.</p> <p><strong>Overview</strong></p> <p>The EDM-HSE Dataset was developed using an algorithmic framework to generate probable drum notations commonly played by EDM music producers. For supervised training with labeled data, a variational mixing technique was applied to the rendered audio files. This method systematically includes or excludes drum notes, assisting the model in recognizing patterns and relationships between drum instruments, thereby enhancing its generalization capabilities.</p> <p>The primary purpose of this dataset is to provide accessible content for machine learning applications in music and audio. Potential use cases include generative music, feature extraction, tempo detection, audio classification, rhythm analysis, drum synthesis, music information retrieval (MIR), sound design and signal processing.</p> <p><strong>Specifications</strong></p> <ul> <li>8,000 audio loops (approximately 17 hours)</li> <li>16-bit WAV format</li> <li>Tempo range: 120–130 BPM</li> <li>Paired label data (WAV + JSON)</li> <li>Variational drum patterns</li> <li>Subgenre styles (Big room, electro, minimal, classic)</li> </ul> <p>A JSON file is provided for referencing and converting MIDI note numbers to text labels. You can update the text labels to suit your preferences.</p> <p><strong>License</strong></p> <p>This dataset was compiled by WaivOps, a crowdsourced music project managed by the sound label company Patchbanks. All recordings have been compiled by verified sources for copyright clearance.</p> <p>The EDM-HSE dataset is licensed under Creative Commons Attribution 4.0 International <a href="https://creativecommons.org/licenses/by/4.0/">(CC BY 4.0)</a>.</p> <p><strong>Additional Info</strong></p> <p>Please note that this dataset has not been fully reviewed and may contain minor notational errors or audio defects.</p> <p>For audio examples or more information about this dataset, please refer to the <a href="https://github.com/patchbanks/WaivOps-EDM-HSE">GitHub repository</a>.</p>
WaivOps EDM-TR9: Open Audio Resources for Machine Learning in Music
<p><strong>EDM-TR9 Dataset</strong></p> <p>EDM-TR9 is an open audio dataset composed of a series of drum recordings in the style of electronic dance music (EDM). This dataset primarily focuses on the distinctive sounds and rhythm patterns of the Roland TR-909 drum machine within the subgenres of dance, house and techno music. The dataset contains 3780 audio loops recorded in uncompressed stereo WAV format, produced with custom drum samples and MIDI-programmed rhythms at various tempo rates.</p> <p><strong>Dataset</strong></p> <p>The primary objective of this dataset is to provide accessible content for machine learning applications in music and audio research. Some potential use cases for this dataset include tempo detection and classification, drum rhythm analysis, audio-to-MIDI conversion, source separation, automated mixing, music information retrieval, AI music generation, sound design and signal processing.</p> <p><strong>Specifications</strong></p> <ul> <li>3780 audio loops (approximately 8 hours)</li> <li>24-bit WAV format</li> <li>BPM labeled</li> <li>Tempo range: 120–140bpm</li> <li>Variational drum patterns</li> <li>EDM drum rhythms</li> </ul> <p><strong>License</strong></p> <p>This dataset was compiled by WaivOps, a crowdsourced music project managed by the sound label company Patchbanks. All recordings have been compiled by verified sources for copyright clearance.</p> <p>The EDM-TR9 dataset is licensed under Creative Commons Attribution 4.0 International <a href="https://creativecommons.org/licenses/by/4.0/">(CC BY 4.0)</a>.</p> <p><strong>Additional Info</strong></p> <p>For audio examples or more information about this dataset, please refer to the <a href="https://github.com/patchbanks/WaivOps-EDM-TR9">GitHub repository</a>.</p>
WaivOps EDM-TR8: Open Audio Resources for Machine Learning in Music
<p><strong>EDM-TR8 Dataset</strong></p> <p>EDM-TR8 is an open audio dataset composed of a series of drum recordings in the style of electronic dance music (EDM). This dataset primarily focuses on the iconic sounds of the Roland TR-808 drum machine with additional electro synth drums. The dataset contains 3,790 audio loops recorded in uncompressed stereo WAV format, generated with custom audio samples and a MIDI dataset used for training symbolic music models.</p> <p><strong>Dataset</strong></p> <p>The primary objective of this dataset is to provide accessible content for machine learning applications in music and audio research. Some potential use cases for this dataset include tempo detection and classification, drum rhythm analysis, audio-to-MIDI conversion, source separation, automated mixing, music information retrieval, AI music generation, sound design and signal processing.</p> <p><strong>Specifications</strong></p> <ul> <li>3790 audio loops (approximately 9 hours)</li> <li>16-bit WAV format</li> <li>BPM labeled</li> <li>Tempo range: 95–130bpm</li> <li>Variational drum patterns</li> <li>Multi-genre rhythm styles</li> </ul> <p><strong>License</strong></p> <p>This dataset was compiled by WaivOps, a crowdsourced music project managed by the sound label company Patchbanks.. All recordings have been compiled by verified sources for copyright clearance.</p> <p>The EDM-TR8 dataset is licensed under Creative Commons Attribution 4.0 International <a href="https://creativecommons.org/licenses/by/4.0/">(CC BY 4.0)</a>.</p> <p><strong>Additional Info</strong></p> <p>For audio examples or more information about this dataset, please refer to the <a href="https://github.com/patchbanks/WaivOps-EDM-TR8">GitHub repository</a>.</p>
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