This paper focuses on the implementation of a continuous control of the degree of articulation (hypo/hyperarticulation) in the framework of HMM-based speech synthesis. The adaptation of a neutral speech synthesizer to generate hypo and hyperarticulated speech using a limited amount of speech data is first studied. This is done using inter-speaker voice adaptation techniques, applied here to int...

The key factors helping people to understand the synthesized voices of text-to-speech system are the naturalness and the intelligibility. However, making more natural voices remains a difficult task because of the speech data’s scarcity. With data limited corpus, prosodic information such as tone, intonation, Part-of-Speech is added to ensure the quality of synthetic speech. In the paper, we in...

Reducing interference noise in a noisy speech recording has been a challenging task for many years yet has a variety of applications, for example, in handsfree mobile communications, in speech recognition, and in hearing aids. Traditional single-channel noise reduction schemes, such as Wiener filtering, do not work satisfactorily in the presence of non-stationary background noise. Alternatively...

This paper describes a technique for modeling and controlling emotional expressivity of speech in HMM-based speech synthesis. A problem of conventional emotional speech synthesis based on HMM is that the intensity of an emotional expression appearing in synthetic speech completely depends on the database used for model training. To take into account the emotional expressivity that listeners act...

In this paper, we describe an HMM-based speech synthesis system in which spectrum, pitch and state duration are modeled simultaneously in a unified framework of HMM. In the system, pitch and state duration are modeled by multi-space probability distribution HMMs and multi-dimensional Gaussian distributions, respectively. The distributions for spectral parameter, pitch parameter and the state du...