Diese Publikation ist nur auf Englisch verfügbar.
Zusammenfassung
The use of prior situational/contextual knowledge about a given task can significantly improve Automatic Speech Recognition (ASR) performance.
This is typically done through adaptation of acoustic or language models if data is available, or using knowledge-based rescoring.
The main adaptation techniques, however, are either domain-specific, which makes them inadequate for other tasks, or static and offline, and therefore cannot deal with dynamic knowledge.
To circumvent this problem, we propose a real-time system which dynamically integrates situational context into ASR.