AI+ Audio™ eLearning

Type product

AI+ Audio™ eLearning

OC ICT
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Opleiderscore: starstarstarstarstar_border 8,2 OC ICT heeft een gemiddelde beoordeling van 8,2 (uit 13 ervaringen)

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Beschrijving

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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

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Nog niet gevonden wat je zocht? Bekijk deze onderwerpen: Audio & Geluid, Apple Final Cut Pro / Express, Adobe Premiere, Pro Tools en Video / Camera.

TRAININGEN VIRTUEEL en individueel volgen? Bel ons voor (gratis) advies 030 7370799

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

Online proctored exam included, with one free retake.
Exam format: 50 questions, 70% passing, 90 minutes, online proctored exam

Access to all materials and exams is provided for 365 days after delivery.

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