Multiclass classification of Parkinson’s disease using cepstral analysis

Author:

Benmalek Elmehdi,Elmhamdi Jamal,Jilbab Abdelilah

Publisher

Springer Science and Business Media LLC

Subject

Computer Vision and Pattern Recognition,Linguistics and Language,Human-Computer Interaction,Language and Linguistics,Software

Reference34 articles.

1. “An Automatic Speaker Recognition System”, http://www.ifp.uiuc.edu/~minhdo/teaching/speaker_recognition .

2. Alcaraz Meseguer, N. (2009) “Speech Analysis for Automatic Speech Recognition “, Thesis submitted to Norwegian University of Science and Technology Department of Electronics and Telecommunications.

3. AStröm, F., & Koker, R. (2011). A parallel neural network approach to prediction of Parkinson’s disease. Expert Systems with Applications, 38(10), 12470–12474.

4. Baken, R. J., & Orlikoff, R. F. (2000). Clinical measurement of speech and voice (2nd edn.). San Diego: Singular Thomson Learning.

5. Benba, A., Jilbab, A., & Hammouch, A. (2016). Voice assessments for detecting patients with Parkinson’s diseases using PCA and NPCA. International Journal of Speech Technology, 19(4), 743–75412.

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