Speech Technology for Lesser-resourced Languages

My research focuses on developing effective speech technology for languages with limited digital resources. This includes transfer learning approaches, multilingual models, and innovative data augmentation techniques to overcome the “data scarcity” problem.

Research Problems

Most speech technology is developed for major world languages with abundant digital resources. However, thousands of languages have limited or no technological support. My work addresses several challenges:

1. Limited training data: How to build effective speech systems with minimal labeled data
2. Cross-lingual transfer: Leveraging knowledge from resource-rich languages
3. Evaluation methodologies: Creating appropriate metrics for low-resource scenarios
4. Cultural preservation: Supporting language vitality through technology

Current Initiatives

This project encompasses several initiatives:

• Text-to-Speech synthesis for languages with limited data
• Speech recognition systems that leverage cross-lingual knowledge transfer
• Phonological feature mapping for related languages
• Methodologies for evaluating speech technology in low-resource contexts