LLMs for Speech Recognition and Synthesis Training Course
Large Language Models (LLMs) are utilized in various artificial intelligence applications, including speech recognition and synthesis, to process and generate human-like text and speech.
This instructor-led, live training (online or onsite) is designed for beginner-level to intermediate-level software developers and data scientists who wish to implement LLMs in speech recognition and synthesis systems for government use.
By the end of this training, participants will be able to:
- Understand the role of LLMs in speech technologies for government applications.
- Implement LLMs for accurate speech recognition and natural-sounding speech synthesis in public sector workflows.
- Integrate LLMs with speech recognition engines and speech synthesizers for enhanced governmental operations.
- Evaluate and improve the performance of speech systems using LLMs to meet governance and accountability standards.
- Stay informed about current trends and future directions in speech technologies relevant to government use.
Format of the Course
- Interactive lecture and discussion focused on governmental needs.
- Lots of exercises and practice tailored for government applications.
- Hands-on implementation in a live-lab environment designed for public sector professionals.
Course Customization Options
- To request a customized training for this course, please contact us to arrange specific content aligned with your agency's requirements.
Course Outline
Introduction to Speech Recognition and Synthesis for Government
- Fundamentals of speech technologies
- Basics of speech recognition systems
- Overview of speech synthesis
Role of LLMs in Speech Technologies for Government
- Understanding LLMs in speech recognition
- LLMs in speech synthesis
- Advantages of LLMs over traditional models
Data for Speech Recognition and Synthesis for Government
- Data collection and processing for speech technologies
- Training data sets for LLMs
- Ethical considerations in data handling
Training LLMs for Speech Applications for Government
- Deep learning techniques in speech recognition
- Neural network architectures for speech synthesis
- Fine-tuning LLMs for specific speech tasks
Implementing LLMs in Speech Systems for Government
- Integration of LLMs with speech recognition engines
- Developing natural-sounding speech synthesizers
- User interface design for speech applications
Testing and Evaluating Speech Systems for Government
- Methods for testing speech recognition accuracy
- Evaluating the naturalness of synthesized speech
- User studies and feedback collection
Challenges and Solutions in Speech Technologies for Government
- Addressing common issues in speech recognition
- Overcoming obstacles in speech synthesis
- Case studies: successful implementations of LLMs
Future Directions in Speech Technologies for Government
- Emerging trends in speech recognition and synthesis
- The role of LLMs in multilingual speech systems
- Innovations and research opportunities
Project and Assessment for Government
- Designing and implementing a speech recognition or synthesis system using LLMs
- Peer reviews and group discussions
- Final assessment and feedback
Summary and Next Steps for Government
Requirements
- An understanding of fundamental programming principles
- Prior experience with Python programming is advantageous but not mandatory
- Familiarity with foundational machine learning and neural network concepts is helpful
Audience for Government
- Software developers
- Data scientists
- Product managers
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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