What does it take to create the Babel Fish, a tool that can help individuals translate speech
between any two languages? While recent breakthroughs in text-based models have …

Artificial Neural Networks (ANNs) were created inspired by the neural networks in the
human brain and have been widely applied in speech processing. The application areas of …

In this article, our recent efforts on directly modeling utterance-level aggregation for speaker
and language recognition is summarized. First, an on-the-fly data loader for efficient network …

Self-supervised learning has been widely exploited to learn powerful speech
representations. The premise of this paper is that these learned self-supervised …

Existing infrared and visible image fusion methods suffer from edge information loss, artifact
introduction, and image distortion. Therefore, a dual-branch network model based on the …

Deep CNN networks have shown great success in various tasks for text-independent
speaker recognition. In this paper, we explore two approaches for modeling long temporal …

We propose two end-to-end neural configurations for language diarization on bilingual code-
switching speech. The first, a BLSTM-E2E architecture, includes a set of stacked …

Identification of the language used in spoken utterances is useful for multiple applications,
eg, assist in directing or automating telephone calls, or selecting which language-specific …

We propose a novel model to hierarchically incorporate phoneme and phonotactic
information for language identification (LID) without requiring phoneme annotations for …

Code-switching (CS) is common in daily conversations where more than one language is
used within a sentence. The difficulties of CS speech recognition lie in alternating languages …