24 citations · 43 across the 4 of their papers we have counts for
6 papers · 1 filter
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…
Lattice-Based Unsupervised Test-Time Adaptation of Neural Network Acoustic Models
Ondrej Klejch, Joachim Fainberg, Peter Bell +1
Acoustic model adaptation to unseen test recordings aims to reduce the mismatch between training and testing conditions. Most adaptation schemes for neural network models require t…
Lattice-based lightly-supervised acoustic model training
Joachim Fainberg, Ondřej Klejch, Steve Renals +1
In the broadcast domain there is an abundance of related text data and partial transcriptions, such as closed captions and subtitles. This text data can be used for lightly supervi…
Talking to myself: self-dialogues as data for conversational agents
Joachim Fainberg, Ben Krause, Mihai Dobre +5
Conversational agents are gaining popularity with the increasing ubiquity of smart devices. However, training agents in a data driven manner is challenging due to a lack of suitabl…
Learning to adapt: a meta-learning approach for speaker adaptation
Ondřej Klejch, Joachim Fainberg, Peter Bell
The performance of automatic speech recognition systems can be improved by adapting an acoustic model to compensate for the mismatch between training and testing conditions, for ex…
Edina: Building an Open Domain Socialbot with Self-dialogues
Ben Krause, Marco Damonte, Mihai Dobre +6
We present Edina, the University of Edinburgh's social bot for the Amazon Alexa Prize competition. Edina is a conversational agent whose responses utilize data harvested from Amazo…