Speaker State Classification Through Speech Processing

Authors(5) :-Anusha Kalluri, Keerthi Kavya, Kavitha Sri Kasula, Anusha Katakamsetty, K. Gowri Raghavendra Narayan

Speech signal is the fastest and the most natural method of correspondence between humans. This fact has motivated researches to consider speech as a quick and proficient strategy for communication among human and machine. Nowadays users interact with smartphones through their verbal language and this is conceivable as a result of Natural Language Processing and Speech Processing. Through speech processing, we can extract information such as emotions, speaker's state, language identification, age, drowsy and soon. The principal content of paper deals with the speaker state classification whether a person is alcoholic (A), non-alcoholic (NA) or completely non-alcoholic (CNA). The database used is Alcohol Language Corpus (ALC). From the database, two types of features known as midterm and short-term features are extracted. Considering midterm features classifiers such as Support Vector Machine, k Nearest Neighbor, Random forest, Gradient Boosting are applied. The outcomes are then pictured to arrange the most alcoholic from non-alcoholic. The comparative study of all these classifiers can be done effectively.

Authors and Affiliations

Anusha Kalluri
UG Scholar, Department of CSE, VVIT, Guntur, Namburu, Andhra Pradesh, India
Keerthi Kavya
UG Scholar, Department of CSE, VVIT, Guntur, Namburu, Andhra Pradesh, India
Kavitha Sri Kasula
UG Scholar, Department of CSE, VVIT, Guntur, Namburu, Andhra Pradesh, India
Anusha Katakamsetty
UG Scholar, Department of CSE, VVIT, Guntur, Namburu, Andhra Pradesh, India
K. Gowri Raghavendra Narayan
Assistant Professor, Department of CSE, VVIT, Guntur Namburu, Andhra Pradesh, India

Natural Language Processing, Speech Processing, Speaker state, Alcoholic, Features, Classifiers

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Publication Details

Published in : Volume 5 | Issue 2 | March-April 2019
Date of Publication : 2019-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 424-431
Manuscript Number : CSEIT195229
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Anusha Kalluri, Keerthi Kavya, Kavitha Sri Kasula, Anusha Katakamsetty, K. Gowri Raghavendra Narayan, "Speaker State Classification Through Speech Processing", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.424-431, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT195229
Journal URL : http://ijsrcseit.com/CSEIT195229

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