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

Módulos

  • 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

Herramientas de IA

  • 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
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