3 papers
cs.SD2025
Miipher-2: A Universal Speech Restoration Model for Million-Hour Scale Data Restoration
Shigeki Karita, Yuma Koizumi, Heiga Zen +3
Training data cleaning is a new application for generative model-based speech restoration (SR). This paper introduces Miipher-2, an SR model designed for million-hour scale data, f…
cs.SD2025
ReverbMiipher: Generative Speech Restoration meets Reverberation Characteristics Controllability
Wataru Nakata, Yuma Koizumi, Shigeki Karita +5
Reverberation encodes spatial information regarding the acoustic source environment, yet traditional Speech Restoration (SR) usually completely removes reverberation. We propose Re…
cs.CL2024
Adaptive Dropout for Pruning Conformers
Yotaro Kubo, Xingyu Cai, Michiel Bacchiani
This paper proposes a method to effectively perform joint training-and-pruning based on adaptive dropout layers with unit-wise retention probabilities. The proposed method is based…