A study of applying Vietnamese voice interaction for a context-aware aviation search engine

Authors

  • Trần Lâm Quân
  • Vũ Tất Thắng

Keywords:

Language model; Acoustic model; Voice Search, Context-aware; Query Suggestion; Data mining

Abstract

Voice searching is the technology underlying in many spoken dialog applications that enable users to access information using spoken queries. With some popular languages like English etc, voice search function is able to help user to search complex voice queries thanks to long time researches for those languages. For Vietnamese language, voice searching has been researched and its results bring some systems that enable user to make simple queries, like number letters. Generally, with a common voice searching look-up system in each language, there are two issues that a smart look-up system has to solve, they are building speech-processing approaches that help user to search complex queries, including some sentences, and researching data-mining approaches to evaluate queries. In this paper, we put efforts to inherit and improve former researches to build a smart look-up systems that help user to search aviation information by voice searching. There are two researches have applied in two steps: firstly, researching statistical models, adaptive algorithms based on Hidden Markov Model (HMM) to build voice interactive functions in Vietnamese, including Speech Recognition and Text To Speech. Secondly, applying data mining techniques to propose a context-aware search engine of Vietnam aviation information. The paper also provides some experimentations of testing the accuracy of this system. Their results show the ability for a Vietnamese voice search system to be applied in practice.

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Published

2014-07-01

How to Cite

Trần Lâm Quân, & Vũ Tất Thắng. (2014). A study of applying Vietnamese voice interaction for a context-aware aviation search engine. Journal of Network and Innovative Computing, 2, 7. Retrieved from https://cspub-jnic.org/index.php/jnic/article/view/74

Issue

Vol. 2 (2014)

Section

Original Article

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