Curriculum learning (CL) or self-paced learning (SPL) represents a recently proposed
learning regime inspired by the learning process of humans and animals that gradually …

We investigate the concept of speaker adaptive training (SAT) in the context of deep neural
network (DNN) acoustic models. Previous studies have shown success of performing …

Abstract Long Short-Term Memory (LSTM) is a recurrent neural network (RNN) architecture
specializing in modeling long-range temporal dynamics. On acoustic modeling tasks, LSTM …

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 …

The large amount of information stored in audio and video repositories makes search on
speech (SoS) a challenging area that is continuously receiving much interest. Within SoS …

Multilingual deep neural networks (DNNs) can act as deep feature extractors and have been
applied successfully to crosslanguage acoustic modeling. Learning these feature extractors …

When deployed in automated speech recognition (ASR), deep neural networks (DNNs) can
be treated as a complex feature extractor plus a simple linear classifier. Previous work has …

Within search-on-speech, Spoken Term Detection (STD) aims to retrieve data from a speech
repository given a textual representation of a search term. This paper presents an …

Acoustic feature similarity between search results has been shown to be very helpful for the
task of spoken term detection (STD). A graph-based re-ranking approach for STD has been …

For low-resource languages, keyword search (KWS) remains challenging due to the lack of
training data. This work aims to bolster KWS performance in low-resource languages by …