The transcription bottleneck is often cited as a major obstacle for efforts to document the
world's endangered languages and supply them with language technologies. One solution …

In modern multilingual societies, there is a demand for multilingual Automatic Speech
Recognition (ASR) and Spoken Term Detection (STD). Multilingual Spoken Term Detection …

Keyword spotting (KWS) for low-resource languages has drawn increasing attention in
recent years. The state-of-the-art KWS systems are based on lattices or Confusion Networks …

We describe the use of text data scraped from the web to augment language models for
Automatic Speech Recognition and Keyword Search for Low Resource Languages. We …

Sleep-disordered breathing (SDB) is a serious and prevalent condition, and acoustic
analysis via consumer devices (eg smartphones) offers a low-cost solution to screening for …

Spoken term detection (STD) aims at retrieving data from a speech repository given a textual
representation of the search term. Nowadays, it is receiving much interest due to the large …

Abstract Deep Neural Networks (DNN) have been largely used and successfully applied in
the context of speaker independent Automatic Speech Recognition (ASR). However, these …

This paper describes in detail the acoustic modeling part of the keyword search system
developed in the Speech Technology Center (STC) for the OpenKWS 2016 evaluation. The …

The IARPA Babel program ran from March 2012 to November 2016. The aim of the program
was to develop agile and robust speech technology that can be rapidly applied to any …

Fast and accurate Automatic Speech Recognition (ASR) is emerging as a key application for
mobile devices. Delivering ASR on such devices is challenging due to the compute …