Topic
- Computing and Processing
- Components, Circuits, Devices and Systems
- Communication, Networking and Broadcast Technologies
- Power, Energy and Industry Applications
- Signal Processing and Analysis
- Robotics and Control Systems
- General Topics for Engineers
- Fields, Waves and Electromagnetics
- Engineered Materials, Dielectrics and Plasmas
- Bioengineering
- Transportation
- Photonics and Electrooptics
- Engineering Profession
- Aerospace
- Geoscience
- Nuclear Engineering
- Career Development
- Emerging Technologies
- Telecommunications
- English for Technical Professionals
Xinjian Li
Affiliation
Language Technologies Institute, Carnegie Mellon University, Pittsburgh, PA, USA
Topic
European Languages,Language Model,Large-scale Datasets,Self-supervised Learning,Speech Recognition,Training Data,Accuracy Drop,Adaptation Stage,Adaptive Method,Adversarial Attacks,Adversarial Examples,Adversarial Perturbations,Adversarial Robustness,Adversarial Training,Alignment Score,Amount Of Training Data,Artificial Neural Network,Audio Data,Ball Of Radius,Baseline Methods,Beam Search,Benchmark,Classification Of Samples,Conjecture,Convex Set,Creative Commons License,Data Preparation,Decision Boundary,Deletion Errors,Direct Translation,Distance Sampling,Efficiency Issues,Efficient Adaptation,Entire Model,Family Language,High-dimensional,Hourly Data,L1-norm,Language Identification,Language Version,Large-scale Sets,Latent Space,Masked Language Model,Master Node,Mean Opinion Score,Minutes Of Data,Monolingual,Multimodal Learning,Multimodal Model,Multimodal Network,
Biography
Xinjian Li (Student Member, IEEE) received the B.S. and M.S. degrees in computer science from the University of Tokyo, Tokyo, Japan, and the Ph.D. degree in language and information technology from Carnegie Mellon University, Pittsburgh, PA, USA. He joined Google as a Research Scientist working on low-resource and multilingual speech recognition.