Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Plan Szkolenia
Introduction to Speech Recognition and Synthesis
- Fundamentals of speech technologies
- Basics of speech recognition systems
- Overview of speech synthesis
Role of LLMs in Speech Technologies
- Understanding LLMs in speech recognition
- LLMs in speech synthesis
- Advantages of LLMs over traditional models
Data for Speech Recognition and Synthesis
- Data collection and processing for speech technologies
- Training data sets for LLMs
- Ethical considerations in data handling
Training LLMs for Speech Applications
- Deep learning techniques in speech recognition
- Neural network architectures for speech synthesis
- Fine-tuning LLMs for specific speech tasks
Implementing LLMs in Speech Systems
- Integration of LLMs with speech recognition engines
- Developing natural-sounding speech synthesizers
- User interface design for speech applications
Testing and Evaluating Speech Systems
- Methods for testing speech recognition accuracy
- Evaluating the naturalness of synthesized speech
- User studies and feedback collection
Challenges and Solutions in Speech Technologies
- Addressing common issues in speech recognition
- Overcoming obstacles in speech synthesis
- Case studies: successful implementations of LLMs
Future Directions in Speech Technologies
- Emerging trends in speech recognition and synthesis
- The role of LLMs in multilingual speech systems
- Innovations and research opportunities
Project and Assessment
- Designing and implementing a speech recognition or synthesis system using LLMs
- Peer reviews and group discussions
- Final assessment and feedback
Summary and Next Steps
Wymagania
- An understanding of basic programming concepts
- Experience with Python programming is recommended but not required
- Familiarity with basic machine learning and neural network concepts is beneficial
Audience
- Software developers
- Data scientists
- Product managers
14 godzin
