Speech-to-text

I've started the main stretch in the implementation of VAaS: the actual coding. Currently, I have done a few different things:

Speech-to-text

I've started with speech-to-text for emotion recognition. Initially, I wanted to have an AI analyze the emotion of the speaker from the direct audio file, and while that still isn't impossible, it is leagues easier to train an AI like BERT to analyze the emotion in the text itself.

But I'm getting ahead of myself here. So far, I've used a simple python library to transcribe a couple of songs' lyrics. You can follow along with me, since I'm planning to make everything I learn into a tutorial.

The first speech-to-text tutorial is here (on Google Colab).

Simple Sentiment Analysis Using BERT

Honestly, I'm still not totally sure how this code works. But, I have taken the pretrained BERT model and run a sentiment analysis on two simple sentences. The goal of the notebook was to identify if those sentences conveyed a positive emotion, or a negative one.

Sentiment Analysis using BERT tutorial is here.



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