Low resourced languages suffer from limited training data and resources. Data
augmentation is a common approach to increasing the amount of training data. Additional …

In this paper we describe the 2016 BBN conversational telephone speech keyword spotting
system; the culmination of four years of research and development under the IARPA Babel …

This paper proposes several improvements to multilingual training of neural network
acoustic models for speech recognition and keyword spotting in the context of low-resource …

Out of the approximately 7000 languages spoken around the world, there are only about
100 languages with Automatic Speech Recognition (ASR) capability. This is due to the fact …

Pluricentric languages are languages that are spoken in at least two countries where they
have an official function and thus develop national varieties with specific linguistic and …

Spoken term detection, especially of out-of-vocabulary (OOV) keywords, benefits from the
use of sub-word systems. We experiment with different language-independent approaches …

Different language modeling approaches are evaluated on two under-resourced,
agglutinative, South African languages; Sesotho and isiZulu. The two languages present …

The main objective of this paper is to describe the system developed for transcription,
keyword spotting and alerting, archival, and retrieval for broadcasted Telugu TV news. Real …

Abstract System combination is a common approach to improving results for both speech
transcription and keyword spotting—especially in the context of low-resourced languages …

We investigate modeling strategies for English code-switched words as found in a Swahili
spoken term detection system. Code switching, where speakers switch language in a …