Introduction to Speech Recognition
Chapter 1: The Foundations of Speech Recognition
What is Automatic Speech Recognition (ASR)?
A Brief History of ASR Systems
The Components of a Speech Recognition Pipeline
Types of Speech Recognition: Speaker-Dependent vs. Speaker-Independent
Types of Speech Recognition: Isolated Word vs. Continuous Speech
How Computers Process Sound: Digital Audio Basics
Introduction to Phonemes and the Building Blocks of Speech
Chapter 2: Processing Audio Signals
From Sound Waves to Digital Data: Sampling and Quantization
Understanding Audio Formats (WAV, MP3, FLAC)
Visualizing Speech: Waveforms and Spectrograms
Pre-emphasis and Framing
Windowing Functions Explained
Introduction to Feature Extraction
Creating Mel-Frequency Cepstral Coefficients (MFCCs)
Hands-on Practical: Visualizing and Processing Audio Files
Chapter 3: Acoustic Modeling
What is an Acoustic Model?
Mapping Sounds to Phonemes
Early Approaches: Gaussian Mixture Models (GMMs)
Hidden Markov Models (HMMs) for Sequential Data
Combining GMMs and HMMs
Introduction to Neural Network-based Acoustic Models
The Role of an Acoustic Model in an ASR System
Chapter 4: Language Modeling
What is a Language Model?
The Problem of Ambiguity in Speech
N-gram Language Models: Bigrams and Trigrams
Calculating Probabilities of Word Sequences
The Concept of Perplexity
How Language Models Improve Accuracy
Introduction to Neural Network Language Models
Chapter 5: Decoding and Putting It All Together
The Role of the Decoder
Finding the Most Likely Sequence of Words
Introduction to Search Algorithms
Understanding the Viterbi Algorithm
The Complete ASR Pipeline: A Review
Evaluating Performance: Word Error Rate (WER)
Common Challenges in Speech Recognition
Chapter 6: Building Your First Speech Recognition Application
Introduction to Speech Recognition APIs and Libraries
Setting Up Your Python Environment
Using a Pre-trained Model for Transcription
Transcribing Audio from a File
Capturing and Transcribing Microphone Input in Real-Time
Handling API Responses and Errors
Practice: Build a Simple Voice Command Tool
Introduction to Speech Recognition APIs and Libraries
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- Robust Speech Recognition via Large-Scale Weak Supervision, Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine McLeavey, and Ilya Sutskever, 2022 arXiv preprint arXiv:2212.04356 DOI: 10.48550/arXiv.2212.04356 - This paper introduces OpenAI's Whisper model, which the section points out as a significant modern open-source ASR model.
- SpeechRecognition Library Documentation, Anthony Zhang and contributors, 2014 (Anthony Zhang (Uberi)) - The official documentation for the Python SpeechRecognition library, presented in the section as the primary tool for beginners.
- Hugging Face Transformers Documentation, Hugging Face and contributors, N/A (Hugging Face) - Official documentation for the Hugging Face transformers library, which is mentioned as a method to run contemporary open-source ASR models like Whisper locally.
- Speech and Language Processing (3rd ed. draft), Daniel Jurafsky and James H. Martin, 2025 (Stanford University) - An authoritative textbook covering speech recognition and natural language processing, providing foundational background for ASR methods.