Qwen3-ASR is an automatic speech recognition system in the QwenLM family, developed to convert spoken language into text with strong accuracy and real-time performance. As a specialized ASR variant of the broader Qwen language model ecosystem, it focuses on capturing reliable transcriptions from audio sources such as recordings, live streams, or conversational inputs while supporting low latency use cases. The architecture combines advanced neural acoustic modeling with context-aware language prediction so that outputs maintain both fidelity to the original speech and grammatical coherence. This makes Qwen3-ASR suitable for voice-driven applications like AI assistants, dictation tools, speech analytics pipelines, and accessibility features, where accurate and fluid transcription is critical.
Features
- Automatic speech-to-text transcription engine
- Neural acoustic modeling for accurate speech capture
- Context-aware language prediction for coherent output
- Tools for audio preprocessing and segmentation
- Support for real-time or batch transcription
- Integrations for embedding ASR in applications
Project Samples
