• Shweta Singh
• Manan Kathuria
• Rutika Sonawane
• Hansraj Kumawat
• Pooja Wale

Speech processing is a prominent issue for researchers since it is employed in the identification and classification of voice disorders. Speech is, without a doubt, the most natural means of communication that people utilize to engage with one another. The absence or degradation of such a medium will pose a significant danger to appropriate understanding between persons. Detecting abnormalities in speech communications is a difficult field of study. Efforts are being made to design an automatic, rapid, cost-effective and non-invasive recognition system which will discriminate such pathologic samples from those of the normal ones. This paper gives the different attempts made by the researchers to detect acoustic features of speech mainly to discriminate normal voices from pathological voices.

Glottal Pathology, Glottal Features, Support Vector Machines (SVM), 12 Mel-Frequency Filter Bank Cepstral Coefficients (MFCC), Zero-Crossing Rate (ZCR).

"Detection of Laryngeal Cancer using Audio Notes", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 3, page no.d164-d169, March-2022, Available :http://www.jetir.org/papers/JETIR2203322.pdf

"Detection of Laryngeal Cancer using Audio Notes", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 3, page no. ppd164-d169, March-2022, Available at : http://www.jetir.org/papers/JETIR2203322.pdf