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Innovation and Education in AI and Audio Processing

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  • Research Projects
    • Personalized Speech Enhancement
      • Collaborative Deep Learning
      • Sparse Mixture of Local Experts
      • Knowledge Distillation for PSE
      • Self-Supervised Learning and Data Purification for PSE
      • TGIF: A Family-Owned Voice AI
    • Music Applications
      • Neural Pitch Correction of Singing Voice
      • SpaIn-Net: Spatially Informed Music Source Separation
      • Don’t Separate, Learn to Remix: End-to-End Neural Remixing
      • Neural Upmixing via Style Transfer
    • Neural Speech and Audio Coding
      • Audio Coding for Machines
      • LaDiffCodec: Generative De-Quantization for Neural Speech Codec via Latent Diffusion
      • Personalized Neural Speech Codec
      • From Hallucination to Articulation: Language Model-Driven Losses for Neural Speech Coding
      • Psychoacoustic Loss Functions for Neural Audio Coding
      • Cross-Module Residual Learning for Neural Audio Coding
      • Source-Aware Neural Audio Coding
    • Collaborative Audio Enhancement
    • Scalable and Efficient AI
      • AD-FlowTSE: Adaptive Deterministic Flow Matching for Target Speaker Extraction
      • BLOOM-Net: Scalability Matters
      • Scalable and Efficient Speech Enhancement Using Modified Cold Diffusion
      • Learning to Hash for Source Separation
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CV

2020 IEEE SPS Best Paper Award

Minje’s paper, “Joint Optimization of Masks and Deep Recurrent Neural Networks for Monaural Source Separation,” was selected for 2020 IEEE SPS Best Paper Award.

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