Module #1 Introduction to Speech Recognition Overview of speech recognition, its applications, and history
Module #2 Speech Production and Acoustics Understanding how speech is produced and the acoustic properties of speech signals
Module #3 Speech Signal Processing Introduction to speech signal processing, including filtering, windowing, and feature extraction
Module #4 Acoustic Features for Speech Recognition Extracting relevant acoustic features from speech signals, such as Mel-Frequency Cepstral Coefficients (MFCCs)
Module #5 Hidden Markov Models (HMMs) for Speech Recognition Introduction to HMMs and their application to speech recognition
Module #6 Gaussian Mixture Models (GMMs) for Speech Recognition Using GMMs for modeling speech patterns and recognition
Module #7 Deep Learning for Speech Recognition Introduction to deep learning techniques for speech recognition, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)
Module #8 Convolutional Neural Networks (CNNs) for Speech Recognition Applying CNNs to speech recognition, including convolutional and pooling layers
Module #9 Recurrent Neural Networks (RNNs) for Speech Recognition Using RNNs for modeling sequential speech patterns and recognition
Module #10 Long Short-Term Memory (LSTM) Networks for Speech Recognition Applying LSTM networks to speech recognition, including forget gates and cell states
Module #11 Language Modeling for Speech Recognition Understanding language models and their role in speech recognition, including n-gram models and neural language models
Module #12 Decoding and Search Algorithms for Speech Recognition Introduction to decoding and search algorithms for speech recognition, including beam search and lattice-based decoding
Module #13 Speech Recognition Systems and Tools Overview of popular speech recognition systems and tools, including open-source and commercial solutions
Module #14 Speech Enhancement and Noise Robustness Techniques for enhancing speech quality and improving noise robustness in speech recognition systems
Module #15 Speaker Recognition and Verification Introduction to speaker recognition and verification, including speaker identification and authentication
Module #16 Speech Recognition for Specific Domains Adapting speech recognition systems for specific domains, including medical, legal, and financial applications
Module #17 Multimodal Speech Processing Integrating speech recognition with other modalities, including vision and gesture recognition
Module #18 Evaluation Metrics and Benchmarks for Speech Recognition Measuring the performance of speech recognition systems using popular evaluation metrics and benchmarks
Module #19 Advanced Topics in Speech Recognition Exploring advanced topics in speech recognition, including end-to-end models and attention-based models
Module #20 Real-World Applications of Speech Recognition Case studies of real-world applications of speech recognition, including voice assistants and speech-to-text systems
Module #21 Ethical Considerations in Speech Recognition Discussing the ethical implications of speech recognition technology, including privacy and bias concerns
Module #22 Future Directions in Speech Recognition Exploring the future of speech recognition, including emerging trends and areas of research
Module #23 Hands-on Exercise:Building a Simple Speech Recognition System Guided exercise in building a simple speech recognition system using popular tools and libraries
Module #24 Hands-on Exercise:Improving Speech Recognition Performance Guided exercise in improving the performance of a speech recognition system using advanced techniques
Module #25 Case Study:Speech Recognition for Medical Applications In-depth case study of speech recognition for medical applications, including transcription and diagnosis
Module #26 Case Study:Speech Recognition for Voice Assistants In-depth case study of speech recognition for voice assistants, including natural language understanding and dialogue management
Module #27 Group Project:Developing a Speech Recognition System Guided group project in developing a speech recognition system for a specific domain or application
Module #28 Guest Lecture:Industry Perspective on Speech Recognition Guest lecture from an industry expert on the current state and future directions of speech recognition technology
Module #29 Final Project Presentations Student presentations of their final projects, including speech recognition systems and applications
Module #30 Course Wrap-Up & Conclusion Planning next steps in Speech Recognition and Processing career
