Developed Speaker Diarization, Speech Sentiment Analysis and Object Character Recognition

1. Getting Started
2. Prerequisites
3. Installation
4. Angular Installation
5. Dataset
6. Screenshots

For Speaker Diarization, Package used :

• pyAudioAnalysis - A Python library for audio feature extraction, classification, segmentation and applications.

For OCR, package used:

• Tesseract - Tesseract is an optical character recognition engine for various operating systems.

• Dependencies for OCR

$ pip install Flask flask-restful SpeechRecognition opencv-python pytesseract

$ pip install -U textblob

• Dependencies for pyAudioAnalysis

$ pip install numpy matplotlib scipy sklearn hmmlearn simplejson eyed3 pydub

• Clone the source of this library:

$ git clone https://github.com/mishranilesh012/Natural_Language_Processing_Techniques.git

• Installing Angular CLI version 6

$ npm install -g @angular/cli@6

• Run within angular directory Natural_Language_Processing_Techniques\Angular\NLP $

$ npm install

• Running Angular

$ npm start

• Open browser on

http://localhost: 4200

Tested Dataset

• OCR Dataset
• Diarization