AI+ Audio™

Experience the power of AI in Audio™ to reinvent music production, elevate sound design, and craft immersive auditory experiences.

* 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 What is AI?
* 1.2 AI in Daily Life: Audio Examples
* 1.3 Basics of Sound Waves, Amplitude, Frequency
* 1.4 Digital Audio Fundamentals Module 2: Harnessing AI Across Audio Domains

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

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

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

* 5.1 Common Audio Issues
* 5.2 AI-based Noise Filtering & Enhancement
* 5.3 Use Cases: Enhancing Audio Quality for Remote Work Calls Using AI Noise Reduction
* 5.4 Case Study: Krisp’s AI-powered Noise Cancellation in Podcast Production
* 5.5 Hands-on: Use Krisp or Adobe Enhance Speech to clean noisy audio Module 6: Emotion & Sentiment Detection from Audio

* 6.1 Introduction to Emotion Detection
* 6.2 AI Models for Emotion Detection: RNNs, LSTMs, CNNs
* 6.3 Challenges: Bias, Multilingual Contexts, Reliability
* 6.4 Use Case: Enhancing Customer Service with Emotion Detection from Speech
* 6.5 Case Study: IBM Watson Tone Analyzer for Real-Time Emotion Recognition
* 6.6 Hands-on: Use IBM Watson Tone Analyzer or similar APIs to analyze speech samples Module 7: Ethical and Privacy Considerations

* 7.1 Deepfakes and Voice Cloning Risks
* 7.2 Privacy and Data Security
* 7.3 Bias and Fairness in Audio AI
* 7.4 Use Case: Implementing Ethical Voice Data Collection and Consent Management
* 7.5 Case Study: Addressing Bias and Privacy in Audio AI under GDPR Compliance
* 7.6 Hands-on: Detect fake audio clips; create an ethical AI checklist Module 8: Advanced Applications & Future Trends

* 8.1 Sound Event Detection & Classification
* 8.2 Audio Search and Indexing
* 8.3 Innovations: Multimodal AI, Edge Computing, 3D Audio
* 8.4 Emerging Careers in Audio AI Tools you will explore

* TensorFlow Audio Recognition
* PyTorch Sound Classification
* Librosa
* OpenAI Jukebox
* Google Magenta Studio
* Audacity AI Plugins
* Adobe Podcast AI Tools
* AIVA
* Wav2Vec
* SpeechBrain
* JUCE Framework
* FL Studio with AI Integrations
* Logic Pro Smart Tools
* Sonible Smart EQ
* Spotify Audio Analysis API
* NVIDIA Riva Speech SDK
* Deep Learning for Audio Toolkit
* AudioLDM
* Sound Design Automation Tools

Exam: 50 questions, 70% passing, 90 minutes, online proctored exam

Included Instructor-led OR Self-paced course + Official exam + Digital badge