AI+ Audio (AP 7010 Self-Paced Training)
Ziele der Schulung
AI+ Audio™ equips learners with the skills to integrate artificial intelligence into audio creation, sound design, and intelligent audio analysis. It focuses on reinventing music production, enhancing audio quality, and crafting immersive auditory experiences using AI tools and techniques. The course covers foundational concepts, practical applications in speech recognition and generative audio, and prepares participants to apply AI across music, media, gaming, and communication domains. What Will You Learn? — Use AI for sound creation, intelligence and recognition, generative/adaptive audio, production techniques, and understand ethical and industry applications.
Zielgruppe Seminar
- Aspiring Audio Engineers
- Music Producers and Composer
- Machine Learning Enthusiasts
- Game and Media Developers
- Tech Innovators and Researchers
Voraussetzungen
- Basic programming knowledge (Python or similar)
- Understanding of audio signal processing
- Machine learning fundamentals
- Comfort with linear algebra and probability
- Experience with audio software tools (e.g., DAWs)
Seminarinhalt
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 for Multilingual Support
- 4.7 Hands-on: Transcribe Audio & Generate Speech
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
- 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 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: Customer Service Emotion Detection from Speech
- 6.5 Case Study: IBM Watson Tone Analyzer in Real-Time Emotion Recognition
- 6.6 Hands-on: Analyze Speech Samples for Emotion
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: Ethical Voice Data Collection and Consent
- 7.5 Case Study: GDPR Compliance in Audio AI
- 7.6 Hands-on: Detect Fake Audio & Create 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
Hinweise
Prüfung und Zertifizierung
- 50 multiple-choice questions
- 90-minute online proctored exam
- Passing score: 70% (35/50)
- Exam covers 8 modules (topics from introduction to advanced trends)
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