Speech brain–computer interfaces (BCIs) have the potential to restore rapid communication
to people with paralysis by decoding neural activity evoked by attempted speech into text, or …

Brain–computer interfaces (BCIs) can restore communication to people who have lost the
ability to move or speak. So far, a major focus of BCI research has been on restoring gross …

This paper presents the machine learning architecture of the Snips Voice Platform, a
software solution to perform Spoken Language Understanding on microprocessors typical of …

With the widespread adoption of deep learning, natural language processing (NLP), and
speech applications in various domains such as finance, healthcare, and government and …

In this paper we describe a method to perform sequencediscriminative training of neural
network acoustic models without the need for frame-level cross-entropy pre-training. We use …

The state-of-the-art neural network architecture named Transformer has been used
successfully for many sequence-tosequence transformation tasks. The advantage of this …

Artificial intelligence has recently experienced remarkable advances, fueled by large
models, vast datasets, accelerated hardware, and, last but not least, the transformative …

This paper proposes and evaluates the hybrid autoregressive transducer (HAT) model, a
time-synchronous encoder-decoder model that preserves the modularity of conventional …

We describe a large vocabulary speech recognition system that is accurate, has low latency,
and yet has a small enough memory and computational footprint to run faster than real-time …

Automated audio captioning, a task that mimics human perception as well as innovatively
links audio processing and natural language processing, has overseen much progress over …