Kayoko Yanagisawa — accepted AI-conference papers

2023

Modelling Low-Resource Accents Without Accent-Specific TTS Frontend

Georgi Tinchev, Marta Czarnowska, Kamil Deja, Kayoko Yanagisawa, Marius Cotescu

ICASSP 2023accepted

This work focuses on modelling a speaker’s accent that does not have a dedicated text-to-speech (TTS) frontend, including a grapheme-to-phoneme (G2P) module. Prior work on modelling accents assumes a phonetic transcription is available for the target accent, which might not be the case for low-resou…

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2016

Multi-stream spectral representation for statistical parametric speech synthesis

Kayoko Yanagisawa, Ranniery Maia, Yannis Stylianou

ICASSP 2016accepted

In statistical parametric speech synthesis such as Hidden Markov Model (HMM) based synthesis, one of the problems is in the over-smoothing of parameters, which leads to a muffled sensation in the synthesised output. In this paper, we propose an approach in which the high frequency spectrum is modell…

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