48 citations · 218 across the 30 of their papers we have counts for
6 papers · 1 filter
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…
ConvS2S-VC: Fully convolutional sequence-to-sequence voice conversion
Hirokazu Kameoka, Kou Tanaka, Damian Kwasny +2
This paper proposes a voice conversion (VC) method using sequence-to-sequence (seq2seq or S2S) learning, which flexibly converts not only the voice characteristics but also the pit…
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…
ACVAE-VC: Non-parallel many-to-many voice conversion with auxiliary classifier variational autoencoder
Hirokazu Kameoka, Takuhiro Kaneko, Kou Tanaka +1
This paper proposes a non-parallel many-to-many voice conversion (VC) method using a variant of the conditional variational autoencoder (VAE) called an auxiliary classifier VAE (AC…
StarGAN-VC: Non-parallel many-to-many voice conversion with star generative adversarial networks
Hirokazu Kameoka, Takuhiro Kaneko, Kou Tanaka +1
This paper proposes a method that allows non-parallel many-to-many voice conversion (VC) by using a variant of a generative adversarial network (GAN) called StarGAN. Our method, wh…
Generative adversarial network-based approach to signal reconstruction from magnitude spectrograms
Keisuke Oyamada, Hirokazu Kameoka, Takuhiro Kaneko +3
In this paper, we address the problem of reconstructing a time-domain signal (or a phase spectrogram) solely from a magnitude spectrogram. Since magnitude spectrograms do not conta…