Overview of Machine Learners in Classifying of Speech Signals
Hemanta Kumar Palo, Lokanath Sarangi · Advances in computational intelligence and robotics book series · 2020
Machine learning (ML) remains a buzzword during the last few decades due to the requirement of a huge amount of data for adequate processing, the continuously surfacing of better innovative and efficient algorithms, and the advent of powerful computers with enormous computation power. The ML algorithms are mostly based on data mining, clustering, classification, and regression approaches for efficient utilization. Many vivid application domains in the field of speech and image signal processing, market forecast, biomedical signal processing, robotics, trend analysis of data, banking and finance sectors, etc. benefits from such techniques. Among these modules, the classification of speech and speaker identification has been a predominant area of research as it has been alone medium of communication via phone. This has made the author to provide an overview of a few state-of-art ML algorithms, their advantages and limitations, including the advancement to enhance the application domain in this field.