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A Universal Multi-Speaker Multi-Style Text-to-Speech via Disentangled Representation Learning based on Rényi Divergence Minimization
This paper presents a universal multi-speaker, multi-style Text-to-Speech (TTS) synthesis system which is able to generate speech from text with speaker characteristics and speaking style similar to a given reference signal.
Dipjyoti Paul
,
Sankar Mukherjee
,
Yannis Pantazis
,
Yannis Stylianou
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Enhancing Speech Intelligibility in Text-To-Speech Synthesis using Speaking Style Conversion
We proposed a novel transfer learning approach using Tacotron and WaveRNN based TTS synthesis to provide high intelligibility gains in speech-shaped noise and competing-speaker noise.
Dipjyoti Paul
,
Muhammed PV Shifas
,
Yannis Pantazis
,
Yannis Stylianou
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Speaker Conditional WaveRNN: Towards Universal Neural Vocoder for Unseen Speaker and Recording Conditions
We propose a variant of WaveRNN, referred to as speaker conditional WaveRNN (SC-WaveRNN). We target towards the development of an efficient universal vocoder even for unseen speakers and recording conditions.
Dipjyoti Paul
,
Yannis Pantazis
,
Yannis Stylianou
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Non-Parallel Voice Conversion Using Weighted Generative Adversarial Networks
We suggest a novel way to train Generative Adversarial Network (GAN) for the purpose of non-parallel, many-to-many voice conversion.
Dipjyoti Paul
,
Yannis Pantazis
,
Yannis Stylianou
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Training Generative Adversarial Networks with Weights
We propose a simple training variation where suitable weights are defined and assist the training of the Generator.
Yannis Pantazis
,
Dipjyoti Paul
,
Yannis Stylianou
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Generalization of Spoofing Countermeasures: a Case Study with ASVspoof 2015 and BTAS 2016 Corpora
This work investigates the generalization capability of spoofing countermeasures in restricted training conditions where speech from broad attack types are left out in the training database.
Dipjyoti Paul
,
Md Sahidullah
,
Goutam Saha
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