60 citations · 170 across the 14 of their papers we have counts for
15 papers · 1 filter
On the Usefulness of Self-Attention for Automatic Speech Recognition with Transformers
Shucong Zhang, Erfan Loweimi, Peter Bell +1
Self-attention models such as Transformers, which can capture temporal relationships without being limited by the distance between events, have given competitive speech recognition…
Stochastic Attention Head Removal: A simple and effective method for improving Transformer Based ASR Models
Shucong Zhang, Erfan Loweimi, Peter Bell +1
Recently, Transformer based models have shown competitive automatic speech recognition (ASR) performance. One key factor in the success of these models is the multi-head attention…
European Language Grid: An Overview
Georg Rehm, Maria Berger, Ela Elsholz +33
With 24 official EU and many additional languages, multilingualism in Europe and an inclusive Digital Single Market can only be enabled through Language Technologies (LTs). Europea…
Multi-scale Octave Convolutions for Robust Speech Recognition
Joanna Rownicka, Peter Bell, Steve Renals
We propose a multi-scale octave convolution layer to learn robust speech representations efficiently. Octave convolutions were introduced by Chen et al [1] in the computer vision f…
Speaker Adaptive Training using Model Agnostic Meta-Learning
Ondřej Klejch, Joachim Fainberg, Peter Bell +1
Speaker adaptive training (SAT) of neural network acoustic models learns models in a way that makes them more suitable for adaptation to test conditions. Conventionally, model-base…
Embeddings for DNN speaker adaptive training
Joanna Rownicka, Peter Bell, Steve Renals
In this work, we investigate the use of embeddings for speaker-adaptive training of DNNs (DNN-SAT) focusing on a small amount of adaptation data per speaker. DNN-SAT can be viewed…