Nowadays speech synthesis or text to speech (TTS), an ability of system to produce human
like natural sounding voice from the written text, is gaining popularity in the field of speech …

Hidden Markov models (HMMs) and Gaussian mixture models (GMMs) are the two most
common types of acoustic models used in statistical parametric approaches for generating …

We introduce a technique for augmenting neural text-to-speech (TTS) with low-dimensional
trainable speaker embeddings to generate different voices from a single model. As a starting …

Conventional approaches to statistical parametric speech synthesis typically use decision
tree-clustered context-dependent hidden Markov models (HMMs) to represent probability …

As two of the five traditional human senses (sight, hearing, taste, smell, and touch), vision
and sound are basic sources through which humans understand the world. Often correlated …

We introduce a technique for augmenting neural text-to-speech (TTS) with lowdimensional
trainable speaker embeddings to generate different voices from a single model. As a starting …

GIOL I5/04(2013.01) A method and system is disclosed for non-parametric speech GIOL
I5/4(2006.01) conversion. A text-to-speech (TTS) synthesis system may GIOL I3/02(2013.01) …

This paper investigates the approaches of building WaveNet vocoders with limited training
data for voice conversion (VC). Current VC systems using statistical acoustic models always …

In this paper, we evaluate the vulnerability of speaker verification (SV) systems to synthetic
speech. The SV systems are based on either the Gaussian mixture model–universal …

(57) ABSTRACT A method and system is disclosed for building a speech database for a text-
to-speech (TTS) synthesis system from multiple speakers recorded under diverse conditions …