Papers by Jaime Lorenzo-Trueba

2 papers
In Other News: a Bi-style Text-to-speech Model for Synthesizing Newscaster Voice with Limited Data (N19-2)

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Challenge: Recent advances in text-to-speech synthesis have enabled researchers to generate high-quality speech with a wide range of prosodic variations.
Approach: They propose a model that can synthesise newscaster-style speech with a few hours of data . they propose to factor in contextual word embeddings and evaluate it against neutral synthesis .
Outcome: The proposed model can synthesise newscaster-style speech with just a few hours of data.
Proteno: Text Normalization with Limited Data for Fast Deployment in Text to Speech Systems (2021.naacl-industry)

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Challenge: Developing Text Normalization systems for Text-to-Speech (TTS) on new languages is hard.
Approach: They propose a novel architecture to facilitate Text Normalization systems for TTS on new languages . they use a granular tokenization mechanism that enables the system to learn majority of classes .
Outcome: The proposed architecture performs comparable with the state-of-the-art systems on English . the proposed system learns most classes from training data and precodes them for other classes .

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