A Web Application for Speech to Text Classification

Project Code :TCMAPY688

Objective

The main objective of the project is to do an application for converting speech to text using deep learning techniques.

Abstract

This document is a guide to the basics of using Speech-to-Text. This conceptual guide covers the types of requests you can make to Speech-to-Text, how to construct those requests, and how to handle their responses. We recommend that all users of Speech-to-Text read this guide and one of the associated tutorials before diving into the API itself. A Speech-to-Text API synchronous recognition request is the simplest method for performing recognition on speech audio data. Speech-to-Text can process up to 1 minute of speech audio data sent in a synchronous request. After Speech-to-Text processes and recognizes all of the audio, it returns a response.

A synchronous request is blocking, meaning that Speech-to-Text must return a response before processing the next request. Speech-to-Text typically processes audio faster than realtime, processing 30 seconds of audio in 15 seconds on average. In cases of poor audio quality, your recognition request can take significantly longer.

 

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

H/W Specifications:

  • Processor  :  I5/Intel Processor
  • RAM :  8GB (min)
  • Hard Disk :  128 GB

S/W Specifications:

  • Operating System  :   Windows 10
  • Technology  :   Python 3.6+
  • IDE                                    :   PyCharm,
  • Data base                           :  MySql
  • Front end                           :  HTML, CSS, JS
  • Libraries Used                   :  Numpy, IO, OS, Flask, pandas

Learning Outcomes

  • What are the soil parameters?
  • what is Ph value?
  • Crud operations.
  • How Internet Works.
  • What type of technology versions are used.
  • Use of HTML, CSS on UI Designs.
  • Data Parsing Front-End to Back-End.
  • Working Procedure.
  • Introduction to basic technologies used for.
  • How project works.
  • Input and Output modules.
  • Frame work use.
  • Python modules.
  • Project Development Skills:
    • Problem analyzing skills.
    • Problem solving skills.
    • Creativity and imaginary skills.
    • Programming skills.
    • Deployment.
    • Testing skills.
    • Debugging skills.
    • Project presentation skills.
    • Thesis writing skills.

Demo Video

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