18 citations · 36 across the 18 of their papers we have counts for
5 papers · 1 filter
Nonparallel Voice Conversion with Augmented Classifier Star Generative Adversarial Networks
Hirokazu Kameoka, Takuhiro Kaneko, Kou Tanaka +1
We previously proposed a method that allows for nonparallel voice conversion (VC) by using a variant of generative adversarial networks (GANs) called StarGAN. The main features of…
Many-to-Many Voice Transformer Network
Hirokazu Kameoka, Wen-Chin Huang, Kou Tanaka +3
This paper proposes a voice conversion (VC) method based on a sequence-to-sequence (S2S) learning framework, which enables simultaneous conversion of the voice characteristics, pit…
ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech
Xin Wang, Junichi Yamagishi, Massimiliano Todisco +37
Automatic speaker verification (ASV) is one of the most natural and convenient means of biometric person recognition. Unfortunately, just like all other biometric systems, ASV is v…
AttS2S-VC: Sequence-to-Sequence Voice Conversion with Attention and Context Preservation Mechanisms
Kou Tanaka, Hirokazu Kameoka, Takuhiro Kaneko +1
This paper describes a method based on a sequence-to-sequence learning (Seq2Seq) with attention and context preservation mechanism for voice conversion (VC) tasks. Seq2Seq has been…
WaveCycleGAN: Synthetic-to-natural speech waveform conversion using cycle-consistent adversarial networks
Kou Tanaka, Takuhiro Kaneko, Nobukatsu Hojo +1
We propose a learning-based filter that allows us to directly modify a synthetic speech waveform into a natural speech waveform. Speech-processing systems using a vocoder framework…