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07/12/2023
Rhythm Modeling for Voice Conversion
Voice conversion aims to transform source speech into a different target...
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05/30/2023
Voice Conversion With Just Nearest Neighbors
Any-to-any voice conversion aims to transform source speech into a targe...
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05/25/2023
Visually grounded few-shot word acquisition with fewer shots
We propose a visually grounded speech model that acquires new words and ...
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11/03/2021
A Comparison of Discrete and Soft Speech Units for Improved Voice Conversion
The goal of voice conversion is to transform source speech into a target...
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08/04/2021
Daft-Exprt: Robust Prosody Transfer Across Speakers for Expressive Speech Synthesis
This paper presents Daft-Exprt, a multi-speaker acoustic model advancing...
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08/02/2021
Analyzing Speaker Information in Self-Supervised Models to Improve Zero-Resource Speech Processing
Contrastive predictive coding (CPC) aims to learn representations of spe...
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12/14/2020
Towards unsupervised phone and word segmentation using self-supervised vector-quantized neural networks
We investigate segmenting and clustering speech into low-bitrate phone-l...
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12/14/2020
Towards localisation of keywords in speech using weak supervision
Developments in weakly supervised and self-supervised models could enabl...
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05/19/2020
Vector-quantized neural networks for acoustic unit discovery in the ZeroSpeech 2020 challenge
In this paper, we explore vector quantization for acoustic unit discover...
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04/07/2020
Online Constrained Model-based Reinforcement Learning
Applying reinforcement learning to robotic systems poses a number of cha...
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10/13/2019
If dropout limits trainable depth, does critical initialisation still matter? A large-scale statistical analysis on ReLU networks
Recent work in signal propagation theory has shown that dropout limits t...
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04/16/2019
Unsupervised acoustic unit discovery for speech synthesis using discrete latent-variable neural networks
For our submission to the ZeroSpeech 2019 challenge, we apply discrete l...
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07/12/2018