This database includes 208 voice samples, from 150 pathological, and 58 healthy voices. The acquired signals consist of a recording of a vocalization of the vowel 'a' five seconds in length without any interruption of sound. All samples were recorded in a quiet (< 30 dB of background noise) and not too dry (humidity greater than 30-40%) room. The voice recordings were made using an appropriate m-health system, Vox4Health, able to acquire in real-time the voice signal by using the microphone of a mobile device. This system was installed on a Samsung Galaxy S4, Android version 5.0.1. It was held at a distance of about 20 cm from the patient at an angle of about 45 degrees. All recordings were sampled at 8000 Hz and their resolution was 32-bit. Additionally, each recording was filtered with an appropriate filter to remove any noise accidentally added during the acquisition. The participants were instructed to articulate the vocal sample, with a constant voice intensity, as they would during a normal conversation. For each subject, certain training tests were performed about two/three times before the recording.

VOICED (VOice ICar fEDerico II) database

De Pietro Giuseppe;Sannino Giovanna;Verde Laura
2018

Abstract

This database includes 208 voice samples, from 150 pathological, and 58 healthy voices. The acquired signals consist of a recording of a vocalization of the vowel 'a' five seconds in length without any interruption of sound. All samples were recorded in a quiet (< 30 dB of background noise) and not too dry (humidity greater than 30-40%) room. The voice recordings were made using an appropriate m-health system, Vox4Health, able to acquire in real-time the voice signal by using the microphone of a mobile device. This system was installed on a Samsung Galaxy S4, Android version 5.0.1. It was held at a distance of about 20 cm from the patient at an angle of about 45 degrees. All recordings were sampled at 8000 Hz and their resolution was 32-bit. Additionally, each recording was filtered with an appropriate filter to remove any noise accidentally added during the acquisition. The participants were instructed to articulate the vocal sample, with a constant voice intensity, as they would during a normal conversation. For each subject, certain training tests were performed about two/three times before the recording.
2018
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Clinical study
Database
Smart healthcare systems
Voice disorders
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/381078
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