Speech Recognition AI Training in Cecil Street, Singapore

This course introduces learners to the fundamentals of speech recognition using artificial intelligence. Participants will explore how AI transforms spoken language into text, understand the architecture behind speech recognition systems, and build hands-on applications using popular tools like Python, OpenAI Whisper, and third-party APIs. The training focuses on real-world use cases such as voice-to-text transcription, live voice command interfaces, and multilingual speech processing.

By the end of the course, learners will have built working prototypes and gained a strong foundation in AI-based voice systems.

Understanding Speech Recognition and Using APIs

Introduction to Speech Recognition

• What is speech recognition?
• History and evolution of voice technology
• Where speech recognition is used today (virtual assistants, subtitles, automation)

How AI-Based Speech Recognition Works

• The basic process: from audio input to text output
• Components: acoustic model, language model, decoder
• Common challenges: background noise, accents, multiple speakers

Introduction to Speech Recognition Tools and APIs

• Overview of available tools and APIs
• Google Speech-to-Text API
• OpenAI Whisper
• Other APIs (AssemblyAI, Azure Speech, AWS Transcribe)
• How to choose the right tool

Advanced Techniques and Real-Time Voice Applications

Preprocessing and Audio Features

• Understanding audio formats and sampling
• Basic audio cleaning: noise reduction
• Feature extraction: MFCCs, spectrograms, mel filters
• Using libraries like librosa and scipy

Working with OpenAI Whisper

• What is Whisper and how it works
• Installation and setup
• Using Whisper CLI and Python version
• Working with multilingual audio files
• Comparing small vs large Whisper models

Real-World Applications of Speech Recognition

• Voice commands for automation
• Caption generation for videos
• Transcribing meetings or podcasts
• Accessibility and assistive tech use cases

Final Exercise and Wrap-Up

• Present or demo your project
• Wrap-up discussion
• Where to go next (resources, APIs, datasets, communities)