A journey through generative music AI with Valerio Velardo

IA Colaborativa - El impacto de los datos en la IA Generativa

IA Abierta – Modelos para potenciar la creatividad musical

IA Ética – Responsabilidad y el futuro de la IA musical colaborativa

Analyzing Singing Voice Expressivity: Focus on Singing Voice Musical Dynamics

Music Identification with Audio Fingerprinting. An Industrial Perspective

Studying a Musical Repertoire with Computational Approaches: The Case of Carnatic Music

Design, Development, and Deployment of Real-Time Drum Accompaniment Systems

Embedded Machine Learning in Musical Instrument Design, by Chris Kiefer

David Toop and Sergi Jordà: open conversation on music and technology

Violin Performance Analysis using Weak Supervision

Deep Audio Representation Learning for Music Using Weak Supervision

High-Resolution Violin Transcription using Weak Labels

Sounds out of place? Score independent detection of conspicouous mistakes in piano performances.

TriAD: Capturing harmonics with 3D Convolutions

TapTamDrum: A Dataset for Dualized Drum Patterns

Efficient Supervised Training of Audio Transformers for Music Representation Learning

Leveraging pre-trained autoencoders for interpretable prototype learning of music audio

Critical art practices within Generative Music AI with Moisés Horta Valenzuela (𝔥𝔢𝔵𝔬𝔯𝔠𝔦𝔰𝔪𝔬𝔰)

Cátedra IA y Música – Presentation

Interpretable Deep-learning Models for Sound Event Detection and Classification

La IA y el ecosistema musical: desafíos, oportunidades y riesgos

Automatic Characterization and Generation of Music Loops and Samples for Electronic Music Production

Music Technology Group - Universitat Pompeu Fabra

Modeling Timbre for Neural Singing Synthesis

Exploration of Music Collections with Audio Embeddings

Real-time music style classification with Essentia

Real-time music auto-tagging in the browser with Essentia.js

PhD thesis of Minz Won

Data-driven Pitch Content Description of Choral Singing Recordings

Continuing CompMusic: New approaches in the computational analysis of Carnatic Music

Enhancing musicality: scientific, technological and practical challenges

Data-driven Musical Version Identification: Accuracy, Scalability, and Bias Perspectives

Audio Quality and Its Impact on Sound and Music Processing

Training Sound Event Classifiers Using Different Types of Supervision

Music Recommender Systems: Taking Into Account The Artists' Perspective

PhD thesis Ángel D. Blanco

Neural Networks for Singing Voice Extraction in Monaural Polyphonic Music Signals

Music Technology Group - Research Challenges

Learning Contextual Tag Embeddings for Cross-Modal Alignment of Audio and Tags

Investigating the efficacy of music version retrieval systems for setlist identification

Loopnet: Musical Loop Synthesis Conditioned On Intuitive Musical Parameters

Multimodal Metric Learning For Tag-Based Music Retrieval

Semi-supervised Learning for Singing Synthesis Timbre

Melon Playlist Dataset: A Public Dataset For Audio-Based Playlist Generation And Music Tagging

Unsupervised Contrastive Learning Of Sound Event Representations

Relative Music Loudness Estimation In TV Broadcast Audio Using Deep Learning

Improving Sound Retrieval in Large Collaborative Collections

Machine Learning and Deep Neural Networks Approach to Modelling Musical Gestures

Audio-visual deep learning methods for musical instrument classification and separation

Exploring Artist Gender Bias in Music Recommendation

Real-time Recitatives-to-Score Alignment

TIV.lib: an open-source library for the tonal description of musical audio

Automatic Identification of Jumps in Music Performances

Cross-Dataset Evaluation of Audio Auto-Tagging Models

Demystifying Differentiable Digital Signal Processing (DDSP)

Can Transient/Non-Transient Separation Improve Instrument Recognition?

A Deeper Dive into the Volume Sensitivity Issue of Singing Voice Detection

Conditioned-U-Net for Singing Voice Separation

We are the Music Technology Group