Speak4it is a voice-enabled local search system currently available for iPhone devices. The natural language understanding (NLU) component is one of the key technology modules in this system. The role of NLU in voice-enabled local search is twofold: (a) parse the automatic speech recognition (ASR) output (1-best and word lattices) into meaningful segments that contribute to high-precision local search, and (b) understand users intent. This paper is concerned with the first task of NLU. In previous work, we had presented a scalable approach to parsing, which is built upon text indexing and search framework, and can also parse ASR lattices. In this paper, we propose an algorithm to improve the baseline by extracting the subjects of the query. Experimental results indicate that lattice-based query parsing outperforms ASR 1-best based parsing by 2.1% absolute and extracting subjects in the query improves the robustness of search.
Cite as: Feng, J., Banglore, S., Gilbert, M. (2009) Role of natural language understanding in voice local search. Proc. Interspeech 2009, 1859-1862, doi: 10.21437/Interspeech.2009-540
@inproceedings{feng09_interspeech,
author={Junlan Feng and Srinivas Banglore and Mazin Gilbert},
title={{Role of natural language understanding in voice local search}},
year=2009,
booktitle={Proc. Interspeech 2009},
pages={1859--1862},
doi={10.21437/Interspeech.2009-540}
}