Spoken content retrieval refers to directly indexing and retrieving spoken content based on
the audio rather than text descriptions. This potentially eliminates the requirement of …

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 …

End-to-end (E2E) approaches to keyword search (KWS) are considerably simpler in terms of
training and indexing complexity when compared to approaches which use the output of …

In this paper, we propose a novel approach to keyword search (KWS) in low-resource
languages, which provides an alternative method for retrieving the terms of interest …

Automatic speech recognition (ASR) systems often need to be developed for extremely low-
resource languages to serve end-uses such as audio content categorization and search …

In this paper, we propose a neural network based distance metric learning method for a
better discrimination in the sequence-matching based keyword search (KWS). In this …

The modeling of text queries as sequences of embeddings for conducting similarity
matching based search within speech features has been recently shown to improve keyword …

In this paper, we propose a novel approach for query modeling using neural networks for
posteriorgram based keyword search (KWS). We aim to help the conventional large …

Process of human-machine interaction is an integral part of everyday human life in a modern
world. The various interfaces are intended to facilitate this interaction and provide maximum …

This paper investigates a weighted finite state transducer (WFST) based syllable decoding
and transduction method for keyword search (KWS), and compares it with sub-word search …