Spoken keyword spotting (KWS) deals with the identification of keywords in audio streams
and has become a fast-growing technology thanks to the paradigm shift introduced by deep …

We present SpecAugment, a simple data augmentation method for speech recognition.
SpecAugment is applied directly to the feature inputs of a neural network (ie, filter bank …

In this paper, we propose a new loss function called generalized end-to-end (GE2E) loss,
which makes the training of speaker verification models more efficient than our previous …

For many years, i-vector based audio embedding techniques were the dominant approach
for speaker verification and speaker diarization applications. However, mirroring the rise of …

In this paper we present a data-driven, integrated approach to speaker verification, which
maps a test utterance and a few reference utterances directly to a single score for verification …

Recently, SpecAugment, an augmentation scheme for automatic speech recognition that
acts directly on the spectrogram of input utterances, has shown to be highly effective in …

Attention-based models have recently shown great performance on a range of tasks, such
as speech recognition, machine translation, and image captioning due to their ability to …

Underground target detection plays an important role in maintaining underground space
security and relies on efficient real-time detection methods. Electromagnetic detection …

Keyword spotting (KWS) constitutes a major component of human-technology interfaces.
Maximizing the detection accuracy at a low false alarm (FA) rate, while minimizing the …

Robust and far-field speech recognition is critical to enable true hands-free communication.
In far-field conditions, signals are attenuated due to distance. To improve robustness to …