Bootstrapping Language Description : The case of Mpiemo (Bantu A, Central African Republic)

• Linguists have long been producing grammatical decriptions of yet undescribed languages. This is a time-consuming process, which has already adapted to improved technology for recording and storage. We present here a novel application of NLP techniques to bootstrap analysis of collected data and speed-up manual selection work. To be more precise, we argue that unsupervised induction of morphology and part-of-speech analysis from raw text data is mature enough to produce useful results. Experiments with Latent Semantic Analysis were less fruitful. We exemplify this on Mpiemo, a so-far essentially undescribed Bantu language of the Central African Republic, for which raw text data was available.

Subject headings

HUMANIORA  -- Språk och litteratur -- Studier av enskilda språk (hsv//swe)

HUMANITIES  -- Languages and Literature -- Specific Languages (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Language Technology (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Keyword

Mpiemo

Bantu A

Central African Republic

NLP

Latent Semantic Analysis

bootstrapping

African languages

Afrikanska språk

Computational linguistics

Datorlingvistik

Acquisition

Machine Learning

Endangered languages

Language modelling

Publication and Content Type

ref (subject category)

kon (subject category)