Abstract--With the proliferation of handheld devices, information access on mobile devices is a topic of growing relevance. This paper presents a system that allows the user to search for information on mobile devices using spoken natural-language queries. We explore several issues related to the creation of this system, which combines state-of-the-art speech-recognition and information-retrieval technologies. This is the first work that we are aware of which evaluates spoken query based information retrieval on a commonly available and well researched text database, the Chinese news corpus used in National Institute of Standards and Technology (NIST)'s TREC-5 and TREC-6 benchmarks. To compare spoken-query retrieval performance for different relevant scenarios and recognition accuracies, the benchmark queries--read verbatim by 20 speakers--were recorded simultaneously through three channels: headset microphone, PDA microphone, and cellular phone. Our results show that for mobile d...
E. Chang, Frank Seide, Helen M. Meng, Zhuoran Chen