88 citations · 308 across the 88 of their papers we have counts for
22 papers · 1 filter
DNN-based ensemble singing voice synthesis with interactions between singers
Hiroaki Hyodo, Shinnosuke Takamichi, Tomohiko Nakamura +2
We propose a singing voice synthesis (SVS) method for a more unified ensemble singing voice by modeling interactions between singers. Most existing SVS methods aim to synthesize a…
BigCodec: Pushing the Limits of Low-Bitrate Neural Speech Codec
Detai Xin, Xu Tan, Shinnosuke Takamichi +1
We present BigCodec, a low-bitrate neural speech codec. While recent neural speech codecs have shown impressive progress, their performance significantly deteriorates at low bitrat…
SaSLaW: Dialogue Speech Corpus with Audio-visual Egocentric Information Toward Environment-adaptive Dialogue Speech Synthesis
Osamu Take, Shinnosuke Takamichi, Kentaro Seki +2
This paper presents SaSLaW, a spontaneous dialogue speech corpus containing synchronous recordings of what speakers speak, listen to, and watch. Humans consider the diverse environ…
RALL-E: Robust Codec Language Modeling with Chain-of-Thought Prompting for Text-to-Speech Synthesis
Detai Xin, Xu Tan, Kai Shen +8
We present RALL-E, a robust language modeling method for text-to-speech (TTS) synthesis. While previous work based on large language models (LLMs) shows impressive performance on z…
Perceptual Quality Enhancement of Sound Field Synthesis Based on Combination of Pressure and Amplitude Matching
Keisuke Kimura, Shoichi Koyama, Hiroshi Saruwatari
A sound field synthesis method enhancing perceptual quality is proposed. Sound field synthesis using multiple loudspeakers enables spatial audio reproduction with a broad listening…
Multichannel Active Noise Control with Exterior Radiation Suppression Based on Riemannian Optimization
Takaaki Kojima, Kazuyuki Arikawa, Shoichi Koyama +1
A multichannel active noise control (ANC) method with exterior radiation suppression is proposed. When applying ANC in a three-dimensional space by using multiple microphones and l…
Kernel-interpolation-based spatial active noise control with exterior radiation suppression
Kazuyuki Arikawa, Shoichi Koyama, Hiroshi Saruwatari
A spatial active noise control (ANC) method based on kernel interpolation of a sound field with exterior radiation suppression is proposed. The aim of spatial ANC is to reduce inco…
Spatial Active Noise Control Method Based On Sound Field Interpolation From Reference Microphone Signals
Kazuyuki Arikawa, Shoichi Koyama, Hiroshi Saruwatari
A spatial active noise control (ANC) method based on the interpolation of a sound field from reference microphone signals is proposed. In most current spatial ANC methods, a suffic…
Kernel interpolation of acoustic transfer functions with adaptive kernel for directed and residual reverberations
Juliano G. C. Ribeiro, Shoichi Koyama, Hiroshi Saruwatari
An interpolation method for region-to-region acoustic transfer functions (ATFs) based on kernel ridge regression with an adaptive kernel is proposed. Most current ATF interpolation…
Duration-aware pause insertion using pre-trained language model for multi-speaker text-to-speech
Dong Yang, Tomoki Koriyama, Yuki Saito +3
Pause insertion, also known as phrase break prediction and phrasing, is an essential part of TTS systems because proper pauses with natural duration significantly enhance the rhyth…
Learning to Speak from Text: Zero-Shot Multilingual Text-to-Speech with Unsupervised Text Pretraining
Takaaki Saeki, Soumi Maiti, Xinjian Li +3
While neural text-to-speech (TTS) has achieved human-like natural synthetic speech, multilingual TTS systems are limited to resource-rich languages due to the need for paired text…
JaCappella Corpus: A Japanese a Cappella Vocal Ensemble Corpus
Tomohiko Nakamura, Shinnosuke Takamichi, Naoko Tanji +2
We construct a corpus of Japanese a cappella vocal ensembles (jaCappella corpus) for vocal ensemble separation and synthesis. It consists of 35 copyright-cleared vocal ensemble son…
Hyperbolic Timbre Embedding for Musical Instrument Sound Synthesis Based on Variational Autoencoders
Futa Nakashima, Tomohiko Nakamura, Norihiro Takamune +2
In this paper, we propose a musical instrument sound synthesis (MISS) method based on a variational autoencoder (VAE) that has a hierarchy-inducing latent space for timbre. VAE-bas…
Region-to-region kernel interpolation of acoustic transfer function with directional weighting
Juliano G. C. Ribeiro, Shoichi Koyama, Hiroshi Saruwatari
A method of interpolating the acoustic transfer function (ATF) between regions that takes into account both the physical properties of the ATF and the directionality of region conf…
Spatial active noise control based on individual kernel interpolation of primary and secondary sound fields
Kazuyuki Arikawa, Shoichi Koyama, Hiroshi Saruwatari
A spatial active noise control (ANC) method based on the individual kernel interpolation of primary and secondary sound fields is proposed. Spatial ANC is aimed at cancelling unwan…
Binaural rendering from microphone array signals of arbitrary geometry
Naoto Iijima, Shoichi Koyama, Hiroshi Saruwatari
A method of binaural rendering from microphone array signals of arbitrary geometry is proposed. To reproduce binaural signals from microphone array recordings at a remote location,…
JSSS: free Japanese speech corpus for summarization and simplification
Shinnosuke Takamichi, Mamoru Komachi, Naoko Tanji +1
In this paper, we construct a new Japanese speech corpus for speech-based summarization and simplification, "JSSS" (pronounced "j-triple-s"). Given the success of reading-style spe…
Multi-speaker Text-to-speech Synthesis Using Deep Gaussian Processes
Kentaro Mitsui, Tomoki Koriyama, Hiroshi Saruwatari
Multi-speaker speech synthesis is a technique for modeling multiple speakers' voices with a single model. Although many approaches using deep neural networks (DNNs) have been propo…
Utterance-level Sequential Modeling For Deep Gaussian Process Based Speech Synthesis Using Simple Recurrent Unit
Tomoki Koriyama, Hiroshi Saruwatari
This paper presents a deep Gaussian process (DGP) model with a recurrent architecture for speech sequence modeling. DGP is a Bayesian deep model that can be trained effectively wit…
DNN-based Speaker Embedding Using Subjective Inter-speaker Similarity for Multi-speaker Modeling in Speech Synthesis
Yuki Saito, Shinnosuke Takamichi, Hiroshi Saruwatari
This paper proposes novel algorithms for speaker embedding using subjective inter-speaker similarity based on deep neural networks (DNNs). Although conventional DNN-based speaker e…
Independent Low-Rank Matrix Analysis Based on Time-Variant Sub-Gaussian Source Model
Shinichi Mogami, Norihiro Takamune, Daichi Kitamura +5
Independent low-rank matrix analysis (ILRMA) is a fast and stable method for blind audio source separation. Conventional ILRMAs assume time-variant (super-)Gaussian source models,…
Independent Deeply Learned Matrix Analysis for Multichannel Audio Source Separation
Shinichi Mogami, Hayato Sumino, Daichi Kitamura +4
In this paper, we address a multichannel audio source separation task and propose a new efficient method called independent deeply learned matrix analysis (IDLMA). IDLMA estimates…