Introduction to Speech Analytics using Python





Data Science is an emerging field. We have seen a lot of ML research within the last few years in the sectors of Predictive Analytics, NLP and Computer Vision. The next emerging field with a lot of scope to deep dive for Data Engineers is - SPEECH.

This workshop would be focused on how an individual can start processing and building models in Sound Domain. With a hands-on and interactive approach, we will understand essential concepts in Speech Analytics along with extensive case- studies and hands-on examples to master state-of-the-art tools, techniques and frameworks for actually applying Speech technologies to solve real- world problems. We will leverage Machine learning and Deep Learning to Classify Voice Data.

Introduction to Speech Analytics :-

  1. Reading Speech Data

    • Audio Signal properties ?

      • Amplitude
      • Wavelength
      • Frequency
      • Sample Rate
      • Windowing
      • Phoneme
    • Reading Speech Wave Features

      • Spectogram
      • MelSpectogram
      • MFCC
  2. Visualization of Speech Data

  3. Transformations in Speech Data

    • Resampling a Speech Wave
    • Frequency and Time Masking a Wave
    • Amplification
    • Low pass/ High pass Filters
    • Equalizing / Normalizing
    • Dither
  4. Hands on Training on Speech To Text

    • Data Pre-Processing and Preparation
    • Creating a CNN + BiDirectional LSTM Model
    • Train the Model
    • Record an input via microphone and change it to Text
  5. Brief Introduction to other Speech Analytics Algorithms

    • Background Noise Removal
    • Sound Modulation
    • Speaker Separation

At the end of the session an attendee would be taking back :

  1. What is Speech and how is it interpreted by a computer

  2. What are the interpretations and transformations one can make on Speech Data.

  3. How to create applications on Speech Data


Basic knowledge of Python

Basics of ML

Video URL:

Speaker Info:

Priya is currently working as a Deputy Manager with Deloitte and has been working in the Data Science industry since the past 4.5 years with experience in working at Innovations & Analytics teams of firms like JP Morgan, HDFC and Syntel. She got her bachelor's from IIT Bombay and attended fellowship program on Product Management in AI at Germany. She has also won Hackathons in India and Germany. Apart from her work she has started her own initiate of a platform which creates customized guides to help people establish their Data Science goals. Her specialization lies in the field of Statistics, Speech Analytics Predictive Analytics and NLP in sectors such as Finance, Retail and Automobile sector.

In addition to her work , Priya had worked as a Corporate trainer for her organization- JP Morgan and had trained more than 200+ employees on technologies such as - Python, Machine Learning and Data Science. She has given a number of talks and training sessions as a part of WiMLDS, Mumbai in colleges - KJ Somaiya, IIT Bombay. She was also invited as a guest lecture at CellStrat AI Labs, Bangalore and Data Conference by WiDS, Noida.

Speaker Links:

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Section: Data Science, Machine Learning and AI
Type: Workshop
Target Audience: Beginner
Last Updated: