SONITRA
A controlled benchmarking toolkit for automatic music transcription that systematically varies acoustic factors to separate algorithmic limitations from recording artefacts.
READ MORE north_eastShayan Dadman
AI-Music Researcher
Intersection of artificial intelligence and musical creativity. Exploring human-AI co-creation through adaptive frameworks and computational rigor. Building systems that listen, learn, and create space for human agency.
Projects
SCOPE (Situated Creative Operation and Process Evaluation)
An evaluation framework for assessing generative AI tools in creative practice by examining situated observation of production workflows rather than just final outputs, developed through my PhD research and validated with professional music producers at UiT, UiO, and NTNU faculties.
READ MORE north_eastLatent Expressions
An interdisciplinary collaboration merging AI research with artistic vision, using StyleGAN-generated faces to address human rights and political identity.
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Learning Normal Patterns in Musical Loops
An unsupervised framework for analyzing audio patterns in musical loops through anomaly detection. Combines HTS-AT feature extraction with Deep SVDD to learn normal patterns without labeled training …
READ MORE north_eastBuilding Tools for Hierarchical Self-Organization
Two complementary Python repositories for training and analyzing Growing Hierarchical Self-Organizing Maps, focusing on design decisions, trade-offs, and practical research workflows.
READ MORE north_eastMIDI Loop Extraction for Symbolic Music Datasets
A Python package for extracting instrument-specific musical loops from MIDI datasets. Implements a modular pipeline for bass, guitar, piano, drums, and synthesizer parts with configurable filtering …
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