66 citations · 217 across the 27 of their papers we have counts for
7 papers · 1 filter
Effect of data reduction on sequence-to-sequence neural TTS
Javier Latorre, Jakub Lachowicz, Jaime Lorenzo-Trueba +4
Recent speech synthesis systems based on sampling from autoregressive neural networks models can generate speech almost undistinguishable from human recordings. However, these mode…
Towards achieving robust universal neural vocoding
Jaime Lorenzo-Trueba, Thomas Drugman, Javier Latorre +5
This paper explores the potential universality of neural vocoders. We train a WaveRNN-based vocoder on 74 speakers coming from 17 languages. This vocoder is shown to be capable of…
The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods
Jaime Lorenzo-Trueba, Junichi Yamagishi, Tomoki Toda +4
We present the Voice Conversion Challenge 2018, designed as a follow up to the 2016 edition with the aim of providing a common framework for evaluating and comparing different stat…
A comparison of recent waveform generation and acoustic modeling methods for neural-network-based speech synthesis
Xin Wang, Jaime Lorenzo-Trueba, Shinji Takaki +2
Recent advances in speech synthesis suggest that limitations such as the lossy nature of the amplitude spectrum with minimum phase approximation and the over-smoothing effect in ac…
High-quality nonparallel voice conversion based on cycle-consistent adversarial network
Fuming Fang, Junichi Yamagishi, Isao Echizen +1
Although voice conversion (VC) algorithms have achieved remarkable success along with the development of machine learning, superior performance is still difficult to achieve when u…
A Spoofing Benchmark for the 2018 Voice Conversion Challenge: Leveraging from Spoofing Countermeasures for Speech Artifact Assessment
Tomi Kinnunen, Jaime Lorenzo-Trueba, Junichi Yamagishi +4
Voice conversion (VC) aims at conversion of speaker characteristic without altering content. Due to training data limitations and modeling imperfections, it is difficult to achieve…
Can we steal your vocal identity from the Internet?: Initial investigation of cloning Obama's voice using GAN, WaveNet and low-quality found data
Jaime Lorenzo-Trueba, Fuming Fang, Xin Wang +3
Thanks to the growing availability of spoofing databases and rapid advances in using them, systems for detecting voice spoofing attacks are becoming more and more capable, and erro…