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.

Ultrafine Particles in Ambient Air of an Urban Area: Dose Implications for Elderly

Due to their detrimental effects on human health, the scientific interest in ultrafine particles (UFP) has been increasing, but available information is far from comprehensive. Compared to the remaining population, the elderly are potentially highly susceptible to the effects of outdoor air pollution. Thus, this study aimed to (1) determine the levels of outdoor pollutants in an urban area with emphasis on UFP concentrations and (2) estimate the respective dose rates of exposure for elderly populations. UFP were continuously measured over 3 weeks at 3 sites in north Portugal: 2 urban (U1 and U2) and 1 rural used as reference (R1). Meteorological parameters and outdoor pollutants including particulate matter (PM10), ozone (O3), nitric oxide (NO), and nitrogen dioxide (NO2) were also measured. The dose rates of inhalation exposure to UFP were estimated for three different elderly age categories: 64–70, 71–80, and >81 years. Over the sampling period levels of PM10, O3 and NO2 were in compliance with European legislation. Mean UFP were 1.7 × 104 and 1.2 × 104 particles/cm3 at U1 and U2, respectively, whereas at rural site levels were 20–70% lower (mean of 1 ×104 particles/cm3). Vehicular traffic and local emissions were the predominant identified sources of UFP at urban sites. In addition, results of correlation analysis showed that UFP were meteorologically dependent. Exposure dose rates were 1.2- to 1.4-fold higher at urban than reference sites with the highest levels noted for adults at 71–80 yr, attributed mainly to higher inhalation rates.

Multidimensional Frailty and Pain in Community Dwelling Elderly

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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.