This paper examines the impact of multilingual (ML) acoustic representations on Automatic
Speech Recognition (ASR) and keyword search (KWS) for low resource languages in the …

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 …

Speech recognition of a language is a key area in the field of pattern recognition. This paper
presents a comprehensive survey on the speech recognition techniques for non-Indian and …

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 …

Current state-of-the-art speech-based user interfaces use data intense methodologies to
recognize free-form speech commands. However, this is not viable for low-resource …

Catastrophic forgetting is a thorny challenge when updating keyword spotting (KWS) models
after deployment. To tackle such challenges, we propose a progressive continual learning …

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 …

Catastrophic forgetting is a thorny challenge when updating keyword spotting (KWS) models
after deployment. This problem will be more challenging if KWS models are further required …

This paper considers an unsupervised data selection problem for the training data of an
acoustic model and the vocabulary coverage of a keyword search system in low-resource …