Journal of Undergraduate Research
Keywords
spoken language identification, Analogical Modeling, AM
College
Humanities
Department
Linguistics and English Language
Abstract
Although it is often repeated, perhaps to the point of becoming cliché, we live in an age of information. Information is readily available, and in a variety of formats, especially electronic formats. Our ability to digitize data, or make it available for computer access, has increased dramatically over the last several decades, due to the exponential growth of computers’ processing power and storage capabilities. However, much of this data is unorganized, and exists in many formats (text, audio, video), and in many different languages. Expert linguists can often identify what language is being spoken in a particular piece of audio data, but human time is expensive and even experts are often error-prone. Using machines to automate the process of spoken language identification would be a tremendous boon, especially in cases where large numbers of language samples must be identified.
Recommended Citation
Stetich, Nicholas A. and Lonsdale, Dr. Deryle
(2013)
"An Approach to Automatic Spoken Language Identification Using Analogical Modeling,"
Journal of Undergraduate Research: Vol. 2013:
Iss.
1, Article 884.
Available at:
https://scholarsarchive.byu.edu/jur/vol2013/iss1/884