18 citations · 31 across the 6 of their papers we have counts for
6 papers
StyleCap: Automatic Speaking-Style Captioning from Speech Based on Speech and Language Self-supervised Learning Models
Kazuki Yamauchi, Yusuke Ijima, Yuki Saito
We propose StyleCap, a method to generate natural language descriptions of speaking styles appearing in speech. Although most of conventional techniques for para-/non-linguistic in…
SpeechGLUE: How Well Can Self-Supervised Speech Models Capture Linguistic Knowledge?
Takanori Ashihara, Takafumi Moriya, Kohei Matsuura +5
Self-supervised learning (SSL) for speech representation has been successfully applied in various downstream tasks, such as speech and speaker recognition. More recently, speech SS…
Zero-shot text-to-speech synthesis conditioned using self-supervised speech representation model
Kenichi Fujita, Takanori Ashihara, Hiroki Kanagawa +2
This paper proposes a zero-shot text-to-speech (TTS) conditioned by a self-supervised speech-representation model acquired through self-supervised learning (SSL). Conventional meth…
SIMD-size aware weight regularization for fast neural vocoding on CPU
Hiroki Kanagawa, Yusuke Ijima
This paper proposes weight regularization for a faster neural vocoder. Pruning time-consuming DNN modules is a promising way to realize a real-time vocoder on a CPU (e.g. WaveRNN,…
Model architectures to extrapolate emotional expressions in DNN-based text-to-speech
Katsuki Inoue, Sunao Hara, Masanobu Abe +2
This paper proposes architectures that facilitate the extrapolation of emotional expressions in deep neural network (DNN)-based text-to-speech (TTS). In this study, the meaning of…
V2S attack: building DNN-based voice conversion from automatic speaker verification
Taiki Nakamura, Yuki Saito, Shinnosuke Takamichi +2
This paper presents a new voice impersonation attack using voice conversion (VC). Enrolling personal voices for automatic speaker verification (ASV) offers natural and flexible bio…