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1:12:13
Studying a Musical Repertoire with Computational Approaches: The Case of Carnatic Music
0:57:10
Design, Development, and Deployment of Real-Time Drum Accompaniment Systems
1:07:26
Embedded Machine Learning in Musical Instrument Design, by Chris Kiefer
1:10:55
David Toop and Sergi Jordà: open conversation on music and technology
0:56:34
Deep Audio Representation Learning for Music Using Weak Supervision
0:52:23
Violin Performance Analysis using Weak Supervision
0:03:39
High-Resolution Violin Transcription using Weak Labels
0:04:00
Sounds out of place? Score independent detection of conspicouous mistakes in piano performances.
0:03:47
TriAD: Capturing harmonics with 3D Convolutions
0:03:59
TapTamDrum: A Dataset for Dualized Drum Patterns
0:04:02
Efficient Supervised Training of Audio Transformers for Music Representation Learning
0:11:22
Leveraging pre-trained autoencoders for interpretable prototype learning of music audio
1:43:29
Critical art practices within Generative Music AI with Moisés Horta Valenzuela (𝔥𝔢𝔵𝔬𝔯𝔠𝔦𝔰𝔪𝔬𝔰)
0:38:38
Cátedra IA y Música – Presentation
0:42:39
Interpretable Deep-learning Models for Sound Event Detection and Classification
0:35:14
La IA y el ecosistema musical: desafíos, oportunidades y riesgos
0:51:31
Automatic Characterization and Generation of Music Loops and Samples for Electronic Music Production
0:48:42
Music Technology Group - Universitat Pompeu Fabra
0:46:57
Modeling Timbre for Neural Singing Synthesis
0:56:23
Exploration of Music Collections with Audio Embeddings
0:02:19
Real-time music auto-tagging in the browser with Essentia.js
0:54:04
PhD thesis of Minz Won
0:52:08
Data-driven Pitch Content Description of Choral Singing Recordings
0:11:59
Continuing CompMusic: New approaches in the computational analysis of Carnatic Music
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