• Empower Audio Innovation with AI: Creative, Practical, Transformative
• Beginner-Friendly Learning: Perfect for newcomers eager to explore AI-powered audio, covering essential concepts with ease
• Comprehensive Skill Building: Includes speech processing, sound enhancement, voice synthesis, and real-world audio AI applications
• Industry-Ready Expertise: Understand how AI is reshaping music, media, entertainment, and communication sectors
• Hands-On Direction: Provides practical frameworks and guided exercises to help you create, analyse, and optimise audio using AI

Module 1: Introduction to AI and Sound

1. 1.1 What is AI?
2. 1.2 AI in Daily Life: Audio Examples
3. 1.3 Basics of Sound Waves, Amplitude, Frequency
4. 1.4 Digital Audio Fundamentals

Module 2: Harnessing AI Across Audio Domains

1. 2.1 AI for Audio Enhancement and Restoration
2. 2.2 AI for Audio Accessibility and Personalization
3. 2.3 AI in Speech and Voice Technologies
4. 2.4 Popular Audio Libraries: Librosa, PyAudio
5. 2.5 Use Case:AI-Driven Real-Time Captioning and Translation for Live Events
6. 2.6 Case Study:Personalized Hearing Aid Adaptation Using AI and Smart Earbuds
7. 2.7 Hands-on: Voice Emotion Detection using Deepgram’s Voice AI Platform

Module 3: Machine Learning & AI for Audio

1. 3.1 Machine Learning Models for Audio Applications
2. 3.2 Deep Learning & Advanced AI Techniques for Audio
3. 3.3 Audio-Specific Architectures: CNNs, RNNs, Transformers
4. 3.4 Transfer Learning in Audio AI
5. 3.5 Use Case: Speech-to-Text Transcription for Medical Records
6. 3.6 Case Study: AI-powered Music Generation with Deep Learning
7. 3.7 Hands-on: Build a Speech-to-Text Model Using TensorFlow

Module 4: Speech Recognition & Text-to-Speech

1. 4.1 Fundamentals of Speech Recognition & Phonetics
2. 4.2 API-based ASR Solutions
3. 4.3 Building Custom ASR Models with Transformers
4. 4.4 Introduction to TTS & Voice Cloning
5. 4.5 Use Case: Automating Meeting Transcriptions with Google Speech-to-Text API
6. 4.6 Case Study: Custom Transformer-based ASR Model for Multilingual Customer Support
7. 4.7 Hands-on: Transcribe audio with an ASR API; generate speech from text

Module 5: Audio Enhancement & Noise Reduction

1. 5.1 Common Audio Issues
2. 5.2 AI-based Noise Filtering & Enhancement
3. 5.3 Use Cases: Enhancing Audio Quality for Remote Work Calls Using AI Noise Reduction
4. 5.4 Case Study: Krisp’s AI-powered Noise Cancellation in Podcast Production
5. 5.5 Hands-on: Use Krisp or Adobe Enhance Speech to clean noisy audio

Module 6: Emotion & Sentiment Detection from Audio

1. 6.1 Introduction to Emotion Detection
2. 6.2 AI Models for Emotion Detection: RNNs, LSTMs, CNNs
3. 6.3 Challenges: Bias, Multilingual Contexts, Reliability
4. 6.4 Use Case: Enhancing Customer Service with Emotion Detection from Speech
5. 6.5 Case Study: IBM Watson Tone Analyzer for Real-Time Emotion Recognition
6. 6.6 Hands-on: Use IBM Watson Tone Analyzer or similar APIs to analyze speech samples

Module 7: Ethical and Privacy Considerations

1. 7.1 Deepfakes and Voice Cloning Risks
2. 7.2 Privacy and Data Security
3. 7.3 Bias and Fairness in Audio AI
4. 7.4 Use Case: Implementing Ethical Voice Data Collection and Consent Management
5. 7.5 Case Study: Addressing Bias and Privacy in Audio AI under GDPR Compliance
6. 7.6 Hands-on: Detect fake audio clips; create an ethical AI checklist

Module 8: Advanced Applications & Future Trends

1. 8.1 Sound Event Detection & Classification
2. 8.2 Audio Search and Indexing
3. 8.3 Innovations: Multimodal AI, Edge Computing, 3D Audio
4. 8.4 Emerging Careers in Audio AI

AI Audio Engineer

Develop intelligent sound systems that adapt to user environments, enhance audio quality, and create dynamic, immersive listening experiences across platforms.

Audio Data Scientist

Analyze sound data to build predictive models for music recommendation, voice recognition, and personalized audio experiences.

AI Sound Designer

Design AI-driven soundscapes, automate mixing and mastering processes, and generate adaptive audio for games, films, and virtual environments.

Audio Technology Manager

Lead the integration of AI tools in music production, post-processing, and sound engineering to streamline workflows and boost creative output.

Chief Audio Innovation Officer (CAIO)

Drive AI transformation in the audio industry by championing intelligent sound design, personalized listening technologies, and next-generation auditory innovation.