Introduction to Speech Recognition Systems
( 25 Modules )

Module #1
Introduction to Speech Recognition
Overview of speech recognition systems, history, and applications

Module #2
Human Speech Production and Perception
Understanding the basics of human speech production and perception

Module #3
Speech Recognition Challenges
Challenges in building speech recognition systems, including variability and noise

Module #4
Speech Recognition System Architecture
Overview of the typical architecture of a speech recognition system

Module #5
Acoustic Signal Processing
Introduction to acoustic signal processing techniques, including filtering and windowing

Module #6
Feature Extraction
Techniques for extracting relevant features from speech signals, including MFCCs and spectrograms

Module #7
Mel-Frequency Cepstral Coefficients (MFCCs)
In-depth look at MFCCs and their role in speech recognition

Module #8
Articulatory and Acoustic Features
Understanding articulatory and acoustic features of speech signals

Module #9
Speech Recognition Models
Overview of speech recognition models, including HMMs, GMMs, and DNNs

Module #10
Hidden Markov Models (HMMs)
In-depth look at HMMs and their application in speech recognition

Module #11
Gaussian Mixture Models (GMMs)
In-depth look at GMMs and their application in speech recognition

Module #12
Deep Neural Networks (DNNs) for Speech Recognition
In-depth look at DNNs and their application in speech recognition

Module #13
Language Modeling
Introduction to language modeling and its role in speech recognition

Module #14
N-Gram Models
In-depth look at N-gram models and their application in language modeling

Module #15
Decoder Algorithms
Overview of decoder algorithms, including Viterbi and beam search

Module #16
Speech Recognition Evaluation Metrics
Introduction to evaluation metrics for speech recognition systems, including WER and SER

Module #17
Robustness and Adaptation
Techniques for improving robustness and adaptation in speech recognition systems

Module #18
Speaker Diarization and Identification
Introduction to speaker diarization and identification techniques

Module #19
Multilingual and Code-Switching Speech Recognition
Challenges and approaches for multilingual and code-switching speech recognition

Module #20
Real-World Applications of Speech Recognition
Overview of real-world applications of speech recognition, including voice assistants and transcription systems

Module #21
Speech Recognition for Specific Domains
Challenges and approaches for speech recognition in specific domains, such as healthcare and finance

Module #22
Ethical Considerations in Speech Recognition
Discussion of ethical considerations in speech recognition, including privacy and bias

Module #23
Speech Recognition System Development
Hands-on experience with developing a speech recognition system using popular toolkits and libraries

Module #24
Advanced Topics in Speech Recognition
Discussion of advanced topics in speech recognition, including end-to-end models and transfer learning

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Introduction to Speech Recognition Systems career

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Introduction to Speech Recognition Systems ( 25 Modules )

Introduction to Speech Recognition Systems
( 25 Modules )