41 citations · 100 across the 25 of their papers we have counts for
5 papers · 1 filter
HumanGAN: generative adversarial network with human-based discriminator and its evaluation in speech perception modeling
Kazuki Fujii, Yuki Saito, Shinnosuke Takamichi +2
We propose the HumanGAN, a generative adversarial network (GAN) incorporating human perception as a discriminator. A basic GAN trains a generator to represent a real-data distribut…
JVS corpus: free Japanese multi-speaker voice corpus
Shinnosuke Takamichi, Kentaro Mitsui, Yuki Saito +3
Thanks to improvements in machine learning techniques, including deep learning, speech synthesis is becoming a machine learning task. To accelerate speech synthesis research, we ar…
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…
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…
Generative Moment Matching Network-based Random Modulation Post-filter for DNN-based Singing Voice Synthesis and Neural Double-tracking
Hiroki Tamaru, Yuki Saito, Shinnosuke Takamichi +2
This paper proposes a generative moment matching network (GMMN)-based post-filter that provides inter-utterance pitch variation for deep neural network (DNN)-based singing voice sy…