Speech Recognition A-Z with Hands-On

Video description

Are you intrigued by how speech recognition is driving the growth of the AI market? This course is a reliable guide if you’re looking to pursue a career as a speech recognition professional and understand industry best practices. You’ll learn the science of applying machine learning algorithms to process large amounts of speech data. As you progress, the course will get you up to speed with automated speech recognition. Later, you’ll delve into speech translation, understanding how to work through speech-to-speech translation. Toward the concluding sections, you’ll focus on voice conversion, exploring everything from Phonetic SID System to speaker identification. Throughout the course, you’ll encounter practice questions to help you reinforce your knowledge.

By the end of this course, you’ll be well-versed with speech recognition and be able to apply what you’ve learned in the real world.

What You Will Learn

  • Develop the skills you need to become a speech recognition professional
  • Get to grips with digitizing and recording speech signals
  • Discover how to build a natural language model
  • Understand the problem statement of converting speech to text
  • Work through speech-to-speech translation
  • Create a speech recognition project


This course is for data analysts, data scientists, machine learning engineers, deep learning engineers, or anyone with basic knowledge of data analysis who has experience in creating models using machine learning.

About The Author

Learnkart Technology Private Limited: Learnkart understands the importance of upskilling and its impact on you. They pride themselves in creating specialized e-learning courses that will not only prepare you for certification exams but also help you gain hands-on knowledge for real-world applications. Thousands of students have developed their skills with Learnkart through a variety of courses, such as PgMP, Risk Management Professional (RMP), speech recognition, Python, Amazon Web Services (AWS), and more. Learnkart regularly adds courses to its portfolio to lend more value to your learning experience.

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Table of contents

  1. Chapter 1 : Speech and Its Types
    1. Introduction
    2. Learning Objectives
    3. Introduction to Speech
    4. Speech Processing and Types of Speech Recognition
    5. What Makes Speech Recognition Hard?
    6. Demo - Audio File Analysis
    7. Digitizing and Recording of Speech Signal
    8. Demo - Digitization and Recording of Speech
    9. Acoustic Phonetics and Articulatory Phonetics
    10. Demo - Human Speech Production
    11. Key Takeaways
  2. Chapter 2 : Automated Speech Recognition
    1. Learning Objectives
    2. Introduction to Audio Signals
    3. Different Types of Signals
    4. Signal Sampling
    5. Demo - Sampling Theorem
    6. Acoustic Modeling
    7. Language Modeling
    8. Building a Basic Language Model
    9. Demo - Audio Signal Feature Extraction
    10. Building a Natural Language Model
    11. Demo - Force Alignment Expectation
    12. Introduction to the Hidden Markov Model
    13. Hidden Markov Model in Speech Recognition
    14. Demo - Spectrum Analysis
    15. Key Takeaways
  3. Chapter 3 : Speech to Text
    1. Learning Objectives
    2. Understanding the Problem Statement
    3. Demo - Speech to Text Modeling
    4. Data Visualization - Part I
    5. Data Visualization - Part II
    6. Data Exploration - Part I
    7. Data Exploration - Part II
    8. Demo - Data Exploration and Visualization
    9. Model Architecture - Part I
    10. Model Architecture - Part II
    11. Key Takeaways
  4. Chapter 4 : Text to Speech
    1. Learning Objectives
    2. Text to Speech System
    3. Text Analysis and Its Methods
    4. Stemming and Lemmatization
    5. Stop Words
    6. Phonetic Analysis
    7. Prosodic Analysis
    8. Waveform Synthesis
    9. Demo - Wave Analysis of Heartbeat Sound
    10. Voice Builder
    11. Key Takeaways
  5. Chapter 5 : Multilingual Speech Processing
    1. Learning Objectives
    2. Understanding Multilingual Speech Processing
    3. Issues in Multilingual Speech Processing
    4. Different Language
    5. Encoding Characters
    6. Demo - Multilingual Speech
    7. Key Takeaways
  6. Chapter 6 : Speech Translation
    1. Learning Objectives
    2. Speech Translation
    3. Speech to Speech Translation
    4. Demo - Speech to Speech Translation
    5. Speech Processing - Interactive Creation and Evaluation (SPICE) Toolkit
    6. Working on Speech to Speech Translation
    7. Key Takeaways
  7. Chapter 7 : Spoken Dialog System
    1. Learning Objectives
    2. Spoken Dialog System
    3. Components of the Dialog System - Part I
    4. Components of the Dialog System - Part II
    5. Voice XML and SSML
    6. Olympus
    7. Deployment
    8. Demo - Voice Building Using a Text Personal Voice Assistant
    9. Key Takeaways
  8. Chapter 8 : Voice Conversion
    1. Learning Objectives
    2. Introduction to Voice Conversion
    3. Automatic Speech Recognition
    4. Phonetic SID System
    5. Speaker De-Identification
    6. Demo - Speaker Identification
    7. Key Takeaways

Product information

  • Title: Speech Recognition A-Z with Hands-On
  • Author(s): Learnkart Technology Private Limited
  • Release date: August 2020
  • Publisher(s): Packt Publishing
  • ISBN: 9781800561700