3 citations · 3 across the 5 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
eess.AS2026
Neural Audio Codec with Adjustable Token Temporal Resolution Using Sampling-Frequency-Independent Convolutional Layers
Tomohiko Nakamura, Wataru Nakata, Kanami Imamura +1
Discrete tokens obtained from neural audio codecs (NACs) have been used as compact representations in audio generation and understanding models. In such token-based systems, token…
cs.SD2026
Dissecting Performance Degradation in Audio Source Separation under Sampling Frequency Mismatch
Kanami Imamura, Tomohiko Nakamura, Kohei Yatabe +1
Audio processing methods based on deep neural networks are typically trained at a single sampling frequency (SF). To handle untrained SFs, signal resampling is commonly employed, b…