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Adam Gabrys

3 accepted papers

2022

Cross-Speaker Style Transfer for Text-to-Speech Using Data Augmentation

ICASSP 2022accepted

We address the problem of cross-speaker style transfer for text-to-speech (TTS) using data augmentation via voice conversion. We assume to have a corpus of neutral non-expressive data from a target speaker and supporting conversational expressive data from different speakers. Our goal is to build a…

Cited by 0SourceScholar
2022

Voice Filter: Few-Shot Text-to-Speech Speaker Adaptation Using Voice Conversion as a Post-Processing Module

ICASSP 2022accepted

State-of-the-art text-to-speech (TTS) systems require several hours of recorded speech data to generate high-quality synthetic speech. When using reduced amounts of training data, standard TTS models suffer from speech quality and intelligibility degradations, making training low-resource TTS system…

Cited by 31SourceScholar
2021

Universal Neural Vocoding with Parallel Wavenet

ICASSP 2021accepted

We present a universal neural vocoder based on Parallel WaveNet, with an additional conditioning network called Audio Encoder. Our universal vocoder offers real-time high-quality speech synthesis on a wide range of use cases. We tested it on 43 internal speakers of diverse age and gender, speaking 2…

Cited by 0SourceScholar