Given the recent surge in developments of deep learning, this paper provides a review of the
state-of-the-art deep learning techniques for audio signal processing. Speech, music, and …

We present a recurrent encoder-decoder deep neural network architecture that directly
translates speech in one language into text in another. The model does not explicitly …

We present a simple yet effective approach to build multilingual speech-to-text (ST)
translation by efficient transfer learning from pretrained speech encoder and text decoder …

Abstract Speech-to-Text (ST) translation pertains to the task of converting speech signals in
one language to text in another language. It finds its application in various domains, such as …

We explore multitask models for neural translation of speech, augmenting them in order to
reflect two intuitive notions. First, we introduce a model where the second task decoder …

Over its three decade history, speech translation has experienced several shifts in its
primary research themes; moving from loosely coupled cascades of speech recognition and …

Multimodal machine translation involves drawing information from more than one modality,
based on the assumption that the additional modalities will contain useful alternative views …

Spoken language translation has recently witnessed a resurgence in popularity, thanks to
the development of end-to-end models and the creation of new corpora, such as Augmented …

Recent advances in deep learning show that end-to-end speech to text translation model is
a promising approach to direct the speech translation field. In this work, we provide an …

Unsupervised representation learning for speech processing has matured greatly in the last
few years. Work in computer vision and natural language processing has paved the way, but …