Speech recognition is the most emerging field of research, as speech is the natural way of
communication. This paper presents the different technologies used for continuous speech …

Acoustic data collection for automatic speech recognition (ASR) purposes is a particularly
challenging task when working with under-resourced languages, many of which are found in …

The NCHLT speech corpus contains wide-band speech from approximately 200 speakers
per language, in each of the eleven official languages of South Africa. We describe the …

Most high-flying and primary means of communication among humans is speech. Despite
the researches and developments in the field of automatic speech recognition the accuracy …

The research work presents experimental work to build a speaker-independent connected
word Hindi speech recognition system using different feature extraction techniques with …

Under-resourced speech recognizers may benefit from data in languages other than the
target language. In this paper, we report how to boost the performance of an Afrikaans …

We report on the development of two reference corpora for the analysis of Sepedi-English
code-switched speech in the context of automatic speech recognition. For the first corpus …

Abstract Grapheme-to-Phoneme (G2P) conversion is the task of predicting the pronunciation
of a word given its graphemic or written form. It is a highly important part of both automatic …

In this paper, we evaluate grapheme-to-phoneme (g2p) models among languages and of
different quality. We created g2p models for Indo-European languages with word …

Posterior based acoustic modeling techniques such as Kullback-Leibler divergence based
HMM (KL-HMM) and Tandem are able to exploit out-of-language data through posterior …