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VOice ICar fEDerico II Database

VOice ICar fEDerico II Database

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Person,Medical Audio

The healthy voices or the presence of each vocal fold's disorders were clinically verified by the medical experts involv......

数据结构 ? 110.1M

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    The healthy voices or the presence of each vocal fold's disorders were clinically verified by the medical experts involved in the project. All diagnoses were made according to indications of the SIFEL protocol, a clinical protocol compiled by the Italian Society of Phoniatrics and Logopaedics. The database includes information such as gender, age, pathology, lifestyle habits (e.g. smoking, alcohol and coffee consummation), occupational status, and the results of two specific medical questionnaires: the Voice Handicap Index (VHI) and Reflux Symptom Index (RSI).

    The medical phonatric examinations, the voice signal acquisitions, and the completion of the medical questionnaires were performed at the ambulatories of Phoniatrics and Videolaryngoscopy of the Hospital University of Naples "Federico II", or at the medical room of the "Institute of High Performance Computing and Networking (ICAR-CNR)". The study started on May 16, 2016 and ended on May 15, 2017.

    The acquired signals consists 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 filltered 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.

    Subjects involved in the study had to be adults aged between 18 and 70 years and able to follow several phases expected in the process. While people aged under 18 and over 70, or with diseases such as folds or upper respiratory tract infections or with neurological disorders were excluded.


    The voice recordings are provided in WFDB format and text format. In addition, the info text files describe the demographics of subjects.

    Database Creators

    The VOICED (VOice ICar fEDerico II) Database was created by: Ugo Cesari (1), Giuseppe De Pietro (2), Elio Marciano (3), Ciro Niri (4), Giovanna Sannino (2), Laura Verde (5).

    1. Department of Otorhinolaryngology, Universityy Hospital (Policlinico) Federico II of Naples, Via S.Pansini, 5 - Naples,Italy
    2. Institute of High Performance Computing and Networking (ICAR-CNR), Via Pietro Castellino, 111-Naples, Italy.
    3. Area of Audiology, Department of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Via S.Pansini, 5-Naples, Italy
    4. Independent Doctor Surgeon Specialized in Audiology and Phoniatrics
    5. Department of Engineering, University of Naples Parthenope, Centro Direzionale di Napoli, Isola C4 - Naples,Italy


    1. Laura Verde
    2. Giovanna Sannino

    When using this resource, please cite the original publication:

    U. Cesari, G. De Pietro, E. Marciano, C. Niri, G. Sannino, and L. Verde. A new database of healthy and pathological voices. Computers & Electrical Engineering, vol. 68, pp. 310-321, 5 2018.

    Please include the standard citation for PhysioNet: (show more options)
    Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.




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