Unified Microphone Conversion: Many-to-Many Device Mapping via Feature-wise Linear Modulation

Autor:	Ryu, Myeonghoon, Oh, Hongseok, Lee, Suji, Park, Han
Rok vydání:	2024
Předmět:	Computer Science - Sound Computer Science - Machine Learning Computer Science - Multimedia Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
Popis:	In this study, we introduce Unified Microphone Conversion, a unified generative framework to enhance the resilience of sound event classification systems against device variability. Building on the limitations of previous works, we condition the generator network with frequency response information to achieve many-to-many device mapping. This approach overcomes the inherent limitation of CycleGAN, requiring separate models for each device pair. Our framework leverages the strengths of CycleGAN for unpaired training to simulate device characteristics in audio recordings and significantly extends its scalability by integrating frequency response related information via Feature-wise Linear Modulation. The experiment results show that our method outperforms the state-of-the-art method by 2.6% and reducing variability by 0.8% in macro-average F1 score. Comment: Currently under review for ICASSP 2025
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2410.18322 Zobrazit plný text záznamu View this record from Arxiv