10 citations · 27 across the 14 of their papers we have counts for
18 papers
Voice Conversion for Lombard Speaking Style with Implicit and Explicit Acoustic Feature Conditioning
Dominika Woszczyk, Manuel Sam Ribeiro, Thomas Merritt +1
Text-to-Speech (TTS) systems in Lombard speaking style can improve the overall intelligibility of speech, useful for hearing loss and noisy conditions. However, training those mode…
Investigating self-supervised features for expressive, multilingual voice conversion
Álvaro Martín-Cortinas, Daniel Sáez-Trigueros, Grzegorz Beringer +7
Voice conversion (VC) systems are widely used for several applications, from speaker anonymisation to personalised speech synthesis. Supervised approaches learn a mapping between d…
AE-Flow: AutoEncoder Normalizing Flow
Jakub Mosiński, Piotr Biliński, Thomas Merritt +2
Recently normalizing flows have been gaining traction in text-to-speech (TTS) and voice conversion (VC) due to their state-of-the-art (SOTA) performance. Normalizing flows are unsu…
Creating New Voices using Normalizing Flows
Piotr Bilinski, Thomas Merritt, Abdelhamid Ezzerg +5
Creating realistic and natural-sounding synthetic speech remains a big challenge for voice identities unseen during training. As there is growing interest in synthesizing voices of…
Comparing normalizing flows and diffusion models for prosody and acoustic modelling in text-to-speech
Guangyan Zhang, Thomas Merritt, Manuel Sam Ribeiro +10
Neural text-to-speech systems are often optimized on L1/L2 losses, which make strong assumptions about the distributions of the target data space. Aiming to improve those assumptio…
Remap, warp and attend: Non-parallel many-to-many accent conversion with Normalizing Flows
Abdelhamid Ezzerg, Thomas Merritt, Kayoko Yanagisawa +6
Regional accents of the same language affect not only how words are pronounced (i.e., phonetic content), but also impact prosodic aspects of speech such as speaking rate and intona…
GlowVC: Mel-spectrogram space disentangling model for language-independent text-free voice conversion
Magdalena Proszewska, Grzegorz Beringer, Daniel Sáez-Trigueros +3
In this paper, we propose GlowVC: a multilingual multi-speaker flow-based model for language-independent text-free voice conversion. We build on Glow-TTS, which provides an archite…
Expressive, Variable, and Controllable Duration Modelling in TTS
Ammar Abbas, Thomas Merritt, Alexis Moinet +5
Duration modelling has become an important research problem once more with the rise of non-attention neural text-to-speech systems. The current approaches largely fall back to rely…
Text-free non-parallel many-to-many voice conversion using normalising flows
Thomas Merritt, Abdelhamid Ezzerg, Piotr Biliński +4
Non-parallel voice conversion (VC) is typically achieved using lossy representations of the source speech. However, ensuring only speaker identity information is dropped whilst all…
Non-Autoregressive TTS with Explicit Duration Modelling for Low-Resource Highly Expressive Speech
Raahil Shah, Kamil Pokora, Abdelhamid Ezzerg +5
Whilst recent neural text-to-speech (TTS) approaches produce high-quality speech, they typically require a large amount of recordings from the target speaker. In previous work, a 3…
Parallel WaveNet conditioned on VAE latent vectors
Jonas Rohnke, Tom Merritt, Jaime Lorenzo-Trueba +4
Recently the state-of-the-art text-to-speech synthesis systems have shifted to a two-model approach: a sequence-to-sequence model to predict a representation of speech (typically m…
Low-resource expressive text-to-speech using data augmentation
Goeric Huybrechts, Thomas Merritt, Giulia Comini +3
While recent neural text-to-speech (TTS) systems perform remarkably well, they typically require a substantial amount of recordings from the target speaker reading in the desired s…
CAMP: a Two-Stage Approach to Modelling Prosody in Context
Zack Hodari, Alexis Moinet, Sri Karlapati +6
Prosody is an integral part of communication, but remains an open problem in state-of-the-art speech synthesis. There are two major issues faced when modelling prosody: (1) prosody…
In Other News: A Bi-style Text-to-speech Model for Synthesizing Newscaster Voice with Limited Data
Nishant Prateek, Mateusz Łajszczak, Roberto Barra-Chicote +5
Neural text-to-speech synthesis (NTTS) models have shown significant progress in generating high-quality speech, however they require a large quantity of training data. This makes…
Comprehensive evaluation of statistical speech waveform synthesis
Thomas Merritt, Bartosz Putrycz, Adam Nadolski +10
Statistical TTS systems that directly predict the speech waveform have recently reported improvements in synthesis quality. This investigation evaluates Amazon's statistical speech…
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…
Analysing Shortcomings of Statistical Parametric Speech Synthesis
Gustav Eje Henter, Simon King, Thomas Merritt +1
Output from statistical parametric speech synthesis (SPSS) remains noticeably worse than natural speech recordings in terms of quality, naturalness, speaker similarity, and intelli…