Speech Recognition
Improving multilingual ASR quality, robustness, and domain adaptation under noisy conditions.
Research Area
Voice Intelligence
Advancing speech systems, conversational AI, and voice-native interfaces through research in low-latency pipelines, interruption handling, robust recognition, and natural response generation across real-world environments.
Core Research Pillars
Conversational AI
Designing turn-taking, context retention, and dialogue strategies for natural spoken interactions.
Speech Synthesis
Building expressive, controllable, and low-latency TTS systems for production use.
Realtime Voice Pipelines
Optimizing end-to-end latency, streaming reliability, and interruption-aware voice processing.
Voice-Native Interfaces
Creating voice-first interaction models for assistants, tools, and embedded intelligent experiences.
Current Focus
01
Low-latency streaming voice runtime
02
Barge-in and interruption management
03
Multilingual conversational quality
04
Evaluation benchmarks for voice reliability
Shape the Future of Voice AI
Collaborate with OpenQCore Research to build reliable, natural, and scalable voice intelligence systems.