Speech-Aware Long Context Pruning and Integration for Contextualized Automatic Speech Recognition

This research paper, published on ArXiv, focuses on improving Automatic Speech Recognition (ASR) by addressing the challenge of long context. The core idea involves pruning and integrating speech-aware information to enhance the model's ability to understand and process extended spoken content. The approach likely aims to improve accuracy and efficiency in ASR systems, particularly in scenarios with lengthy or complex utterances.

• •Focuses on improving Automatic Speech Recognition (ASR).
• •Addresses the challenge of long context in speech recognition.
• •Employs pruning and integration techniques.
• •Aims to enhance accuracy and efficiency in ASR systems.