4 accepted papers
Automatic evaluation of the quality of synthetic speech has the potential to serve as a cheaper and less time-consuming alternative to standard listening tests. In this paper, we present our contribution to the ongoing research: a system for automatic prediction of the mean opinion score (MOS) given…
In this paper, we continue to investigate the use of machine learning for the automatic detection of glottal closure instants (GCIs) from raw speech. We compare several deep one-dimensional convolutional neural network architectures on the same data and show that the InceptionV3 model yields the bes…
In this paper, we continue to investigate the use of classifiers for the automatic detection of glottal closure instants (GCIs) from the speech signal. We focus on extreme gradient boosting (XGB), a fast and powerful implementation of a gradient boosting algorithm. We show that XGB outperforms other…
In this paper, we analyze how much, how consistent and how accurate data WaveNet-based speech synthesis method needs to be able to generate speech of good quality. We do this by adding artificial noise to the description of our training data and observing how well WaveNet trains and produces speech.…