8 papers
Online Algorithms for Independent Low-Rank Matrix Analysis and Rank-Constrained Spatial Covariance Matrix Estimation Based on Maximum Weighted Likelihood Estimation
Yuto Ishikawa, Norihiro Takamune, Tomohiko Nakamura +4
Real-time multichannel speech extraction (MSE) under diffuse noise conditions is an important task with a wide range of applications, such as speech recognition and hearing aids. I…
Lead Vocal Separation from Vocal Ensemble Mixtures Using Phoneme Alignment
Yuma Narahata, Tomohiko Nakamura, Yuki Saito +1
Contemporary a cappella singing often has a lead-and-accompaniment texture, where the lead vocal (Vo) part carries the main melody and the remaining vocal parts provide accompanime…
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…
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…
Drum-to-Vocal Percussion Sound Conversion and Its Evaluation Methodology
Rinka Nobukawa, Makito Kitamura, Tomohiko Nakamura +2
This paper defines the novel task of drum-to-vocal percussion (VP) sound conversion. VP imitates percussion instruments through human vocalization and is frequently employed in con…
Multi-Sampling-Frequency Naturalness MOS Prediction Using Self-Supervised Learning Model with Sampling-Frequency-Independent Layer
Go Nishikawa, Wataru Nakata, Yuki Saito +3
We introduce our submission to the AudioMOS Challenge (AMC) 2025 Track 3: mean opinion score (MOS) prediction for speech with multiple sampling frequencies (SFs). Our submitted mod…
Hyperbolic Embeddings for Order-Aware Classification of Audio Effect Chains
Aogu Wada, Tomohiko Nakamura, Hiroshi Saruwatari
Audio effects (AFXs) are essential tools in music production, frequently applied in chains to shape timbre and dynamics. The order of AFXs in a chain plays a crucial role in determ…
Sampling-Frequency-Independent Universal Sound Separation
Tomohiko Nakamura, Kohei Yatabe
This paper proposes a universal sound separation (USS) method capable of handling untrained sampling frequencies (SFs). The USS aims at separating arbitrary sources of different ty…