788 citations · 938 across the 35 of their papers we have counts for
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Wavehax: Aliasing-Free Neural Waveform Synthesis Based on 2D Convolution and Harmonic Prior for Reliable Complex Spectrogram Estimation
Reo Yoneyama, Atsushi Miyashita, Ryuichi Yamamoto +1
Neural vocoders often struggle with aliasing in latent feature spaces, caused by time-domain nonlinear operations and resampling layers. Aliasing folds high-frequency components in…
Description-based Controllable Text-to-Speech with Cross-Lingual Voice Control
Ryuichi Yamamoto, Yuma Shirahata, Masaya Kawamura +1
We propose a novel description-based controllable text-to-speech (TTS) method with cross-lingual control capability. To address the lack of audio-description paired data in the tar…
SVDD 2024: The Inaugural Singing Voice Deepfake Detection Challenge
You Zhang, Yongyi Zang, Jiatong Shi +3
With the advancements in singing voice generation and the growing presence of AI singers on media platforms, the inaugural Singing Voice Deepfake Detection (SVDD) Challenge aims to…
CtrSVDD: A Benchmark Dataset and Baseline Analysis for Controlled Singing Voice Deepfake Detection
Yongyi Zang, Jiatong Shi, You Zhang +8
Recent singing voice synthesis and conversion advancements necessitate robust singing voice deepfake detection (SVDD) models. Current SVDD datasets face challenges due to limited c…
Audio-conditioned phonemic and prosodic annotation for building text-to-speech models from unlabeled speech data
Yuma Shirahata, Byeongseon Park, Ryuichi Yamamoto +1
This paper proposes an audio-conditioned phonemic and prosodic annotation model for building text-to-speech (TTS) datasets from unlabeled speech samples. For creating a TTS dataset…
LibriTTS-P: A Corpus with Speaking Style and Speaker Identity Prompts for Text-to-Speech and Style Captioning
Masaya Kawamura, Ryuichi Yamamoto, Yuma Shirahata +2
We introduce LibriTTS-P, a new corpus based on LibriTTS-R that includes utterance-level descriptions (i.e., prompts) of speaking style and speaker-level prompts of speaker characte…
Noise-Robust Voice Conversion by Conditional Denoising Training Using Latent Variables of Recording Quality and Environment
Takuto Igarashi, Yuki Saito, Kentaro Seki +4
We propose noise-robust voice conversion (VC) which takes into account the recording quality and environment of noisy source speech. Conventional denoising training improves the no…
SRC4VC: Smartphone-Recorded Corpus for Voice Conversion Benchmark
Yuki Saito, Takuto Igarashi, Kentaro Seki +4
We present SRC4VC, a new corpus containing 11 hours of speech recorded on smartphones by 100 Japanese speakers. Although high-quality multi-speaker corpora can advance voice conver…
SVDD Challenge 2024: A Singing Voice Deepfake Detection Challenge Evaluation Plan
You Zhang, Yongyi Zang, Jiatong Shi +5
The rapid advancement of AI-generated singing voices, which now closely mimic natural human singing and align seamlessly with musical scores, has led to heightened concerns for art…