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Keitaro Tanaka

2 accepted papers

2025

Formula-Supervised Sound Event Detection: Pre-Training Without Real Data

ICASSP 2025accepted

In this paper, we propose a novel formula-driven supervised learning (FDSL) framework for pre-training an environmental sound analysis model by leveraging acoustic signals parametrically synthesized through formula-driven methods. Specifically, we outline detailed procedures and evaluate their effec…

Cited by 0SourceScholar
2021

Pitch-Timbre Disentanglement Of Musical Instrument Sounds Based On Vae-Based Metric Learning

ICASSP 2021accepted

This paper describes a representation learning method for disentangling an arbitrary musical instrument sound into latent pitch and timbre representations. Although such pitch-timbre disentanglement has been achieved with a variational autoencoder (VAE), especially for a predefined set of musical in…

Cited by 0SourceScholar