Tutorial #2

Part I: Foundations and Recent Advances (60 minutes)

• Foundational theories and review of traditional methods in speaker modeling
• Evolution of speaker representation techniques in the deep learning era
  • From i-vector to various deep speaker representations
  • Applications of self-supervised and semi-supervised learning in speaker modeling
  • Analysis of speaker representation capabilities in foundation speech models
  • Leveraging pretrained large models

Part II: Applications Beyond Recognition (60 minutes)

• Speaker-adaptive speech synthesis
  • Voice cloning technologies and ethical considerations
  • Speaker representation in few-shot and zero-shot speech synthesis
• Personalized voice conversion systems
• Speaker perception in multimodal human-computer interaction
• Target speaker speech processing
  • Target speaker extraction
  • Target speaker speech recognition
  • Target speaker verification
  • Personalized VAD

Part III: Challenges and Countermeasures (30 minutes)

• Domain adaptation and domain-invariant learning
• Privacy-preserving speaker representations
• Robustness and adversarial attack defense
• Computational efficiency and model compression
• Explainability techniques and methods

Part IV: Practical Implementation (30 minutes)

• Introduction to tools and frameworks
  • Wespeaker toolkit for speaker embedding learning
  • Wesep toolkit for target speech extraction
• Case studies and demonstrations
• Interactive discussion and Q&A session