Automatic Language Identification: A Review/Tutorial
| Citations: | 6 - 0 self |
BibTeX
@MISC{Muthusamy_automaticlanguage,
author = {Yeshwant K. Muthusamy and Etienne Barnard and Ronald A. Cole},
title = {Automatic Language Identification: A Review/Tutorial},
year = {}
}
OpenURL
Abstract
Introduction 1.1 The Problem Automatic language identification (language ID for short) is the problem of identifying the language being spoken from a sample of speech by an unknown speaker. As with speech recognition, humans are the most accurate language identification systems in the world today. Within seconds of hearing speech, people are able to determine whether it is a language they know. If it is a language with which they are not familiar, they often can make subjective judgments as to its similarity to a language they know, e.g., "sounds like German". Languages have characteristic sound patterns; they are described subjectively as "singsong", "rhythmic", "guttural", "nasal" etc. Languages differ in the inventory of phonological units (speech sound categories) used to produce words, the frequency of occurrence of these units, and the order in which they occur in words. The presence of individual sounds, such as the "clicks" found in some sub-Saharan African la







