activity
20202026
most citedMetasurfaces for Efficient Digital Noise Absorption

5 citations · 5 across the 5 of their papers we have counts for

collaborators

7 papers

eess.AS2026

Downstream-Task-Aware Unified Source Separation

Yoshiki Mitsui, Ryo Aihara, Tatsuhiko Saito +5

Task-aware unified source separation (TUSS) enables a single model to handle diverse separation tasks by conditioning on input prompts. However, conventional TUSS does not account…

eess.AS2025

SUNAC: Source-aware Unified Neural Audio Codec

Ryo Aihara, Yoshiki Masuyama, Francesco Paissan +3

Neural audio codecs (NACs) provide compact representations that can be leveraged in many downstream applications, in particular large language models. Yet most NACs encode mixtures…

cs.SD2025

FlexIO: Flexible Single- and Multi-Channel Speech Separation and Enhancement

Yoshiki Masuyama, Kohei Saijo, Francesco Paissan +6

Speech separation and enhancement (SSE) has advanced remarkably and achieved promising results in controlled settings, such as a fixed number of speakers and a fixed array configur…

eess.AS2025

Exploring Disentangled Neural Speech Codecs from Self-Supervised Representations

Ryo Aihara, Yoshiki Masuyama, Gordon Wichern +2

Neural audio codecs (NACs), which use neural networks to generate compact audio representations, have garnered interest for their applicability to many downstream tasks -- especial…

cs.SD2025

FasTUSS: Faster Task-Aware Unified Source Separation

Francesco Paissan, Gordon Wichern, Yoshiki Masuyama +4

Time-Frequency (TF) dual-path models are currently among the best performing audio source separation network architectures, achieving state-of-the-art performance in speech enhance…

eess.AS2025

Factorized RVQ-GAN For Disentangled Speech Tokenization

Sameer Khurana, Dominik Klement, Antoine Laurent +13

We propose Hierarchical Audio Codec (HAC), a unified neural speech codec that factorizes its bottleneck into three linguistic levels-acoustic, phonetic, and lexical-within a single…

physics.app-ph2020★ 5 cited

Metasurfaces for Efficient Digital Noise Absorption

Ryoya Aihara, Hiroki Wakatsuchi

We numerically demonstrate two types of metasurface absorbers to efficiently absorb digital signals. First, we show that the digital waveforms used in this study contain not only a…