In this paper, we propose a joint federated learning (FL) and personalization method for on-
device ASR adaptation. Starting with a Conformer-based RNN-T as the ASR model …

Radical progress in the field of deep learning (DL) has led to unprecedented accuracy in
diverse inference tasks. As such, deploying DL models across mobile platforms is vital to …

This paper addresses spoken language understanding (SLU) on microcontroller-like
embedded devices, integrating on-device execution with cloud offloading in a novel fashion …

The unprecedented performance of deep neural networks (DNNs) has led to large strides in
various Artificial Intelligence (AI) inference tasks, such as object and speech recognition …

Transformer-based speech recognition (ASR) model with deep layers exhibited significant
performance improvement. However, the model is inefficient for deployment on resource …

This paper addresses spoken language understanding (SLU) on microcontroller-like
embedded devices, integrating on-device execution with cloud offloading in a novel fashion …

The current largest open-source generic automatic speech recognition (ASR) system for
Dutch, Kaldi_NL, does not include a domain-specific healthcare jargon in the lexicon …

In this work, development of an efficient optimized Automatic Speech Recognition (ASR)
system is done by leveraging methodologies. This study focuses on knowledge distillation, a …

In this paper we present the currently running PDI-SSH project Homo Medicinalis (HoMed),
in which we use machine learning to build an Automatic Speech Recognition (ASR) …