A Context-Aware Language Model for Spoken Query Retrieval

摘要

This paper concentrates on the problem of designing and developing a spoken query retrieval (SQR) system to access large document databases via voice. The main challenge is to identify and address issues related to the adaptation and scalability of integrating automatic speech recognition (ASR) and information retrieval (IR). In this paper, a Context Aware Language Model (CALM) framework allowing information retrieval to large document databases via voice is presented and findings from a research study using the framework will be discussed as well.