Work

Using sub-word n-gram models for dealing with OOV in large vocabulary speech recognition for Latvian

Year: 2015

Type: article

Abstract: In the Latvian language, one word can have tens or even hundreds of surface forms.This is a serious problem for large vocabulary speech recognition.Inclusion of every form in vocabulary will make it intractable, but, on the other hand, even with a vocabulary of 400K, the out-ofvocabulary (OOV) rate will be very high.In this paper, the authors investigate the possibility of using sub-word vocabularies where words are split into frequent and common parts.The results of our experiment show that this allows to significantly reduce the OOV rate.

Source: DSpace repository (University of Tartu)

Authors: Askars Salimbajevs, Jevgenijs Strigins

Institution: Tilde (Latvia)

Language: English

Topic: Speech Recognition and Synthesis

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2128474846

FWCI: 0.59

Cites: 16

Cited by: 3

Related to: 10