Speech Recognition Learning Framework for Non-Native English Accent
Mihir Thakkar, Susan Elias, Ashwin Ashok · 2019
Accent is a distinctive way of pronouncing a language, especially one associated with a particular country, area or social class. While dialects are usually spoken by groups united by geography or class and are a variety of same language differing in vocabulary and grammar as well as pronunciation, the accent is how the same language is spoken differently by people of different ethnicities. Accent plays a vital role when it comes to speech recognition by voice assistance systems. The modern-day voice assistant systems tend to misinterpret the words spoken by a person with a strong accent influenced by his native language. Machine learning algorithms, especially Support Vector Machine (SVM) and Random Forest when applied on a proper training set can play a vital role in the classification of accent. We propose in this paper the learning framework for speech recognition of Indian accent by analysing the features of Indian accented English and classifying based on sounds that are typical to Indian accented English.