GitHub repository: AmalVijayan/SpeechClassifier
Primary language: Jupyter Notebook
Created: 2019-12-10T11:48:17Z
Description: Text Classification is one of the most common problems in NLP. In the past few years, there have been numerous successful attempts which gave rise to many state-of-the-art language models that is capable of performing the classification task with mind boggling accuracy and precision. Text classification powers many real world applications from simple spam filtering to voice assistants like Alexa. These applications have the capability to classify the user’s input to understand the context of spoken words.  In this article, we will build on the basic idea of giving the machine the power to listen to human speech and classify what the person is talking about.  In one of our previous tutorials we talked about a library called Simple Transformers that makes it effortless to implement many transformer based state-of-the-art language models. We used the library to classify any number of input texts into one of the following four news sections   Politics Technology Entertainment Business  We will use the same classifier to classify what you speak into one of those four categories effortlessly with very minor changes in code.