On the development of an automatic voice pleasantness classification and intensity estimation system

In the last few years, the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems, the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how pleasant is a voice from a perceptual point of view when the final application is a speech based interface. In this paper we present an objective definition for voice pleasantness based on the composition of a representative feature subset and a new automatic voice pleasantness classification and intensity estimation system. Our study is based on a database composed by European Portuguese female voices but the methodology can be extended to male voices or to other languages. In the objective performance evaluation the system achieved a 9.1% error rate for voice pleasantness classification and a 15.7% error rate for voice pleasantness intensity estimation.

ezGo: A voice operated wheelchair with biosignal monitoring for home environments

In this paper we present ezGo, an electric powered wheelchair with a speech based interface and biosignal monitoring instrumentation. The user can use the voice, a natural communication method, for controlling the chair movement and obtain information about his health. Additionally a set of semi-autonomous modes with macro recording enable the execution of navigation tasks with little effort and improved precision. The main purpose of the system is to provide severely disabled persons with an assistive device that can improve their confidence and daily independence. The obtained results on usability tests showed that users consider ezGo a valuable help on their daily tasks and a very desirable addition to standard wheelchairs.

An automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference

In the last few years the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how good is a voice when the application is a speech based interface. In this paper we present a new automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference. Our study is based on a multi-language database composed by female voices. In the objective performance evaluation the system achieved a 7.3% error rate.