Search Results for author: Brendan Shillingford

Found 14 papers, 5 papers with code

Composing RNNs and FSTs for Small Data: Recovering Missing Characters in Old Hawaiian Text

no code implementations24 Jul 2022 Oiwi Parker Jones, Brendan Shillingford

In contrast to the older writing system of the 19th century, modern Hawaiian orthography employs characters for long vowels and glottal stops.

Reading Comprehension Transliteration

Restoring and attributing ancient texts using deep neural networks

2 code implementations Nature 2022 Yannis Assael, Thea Sommerschield, Brendan Shillingford, Mahyar Bordbar, John Pavlopoulos, Marita Chatzipanagiotou, Ion Androutsopoulos, Jonathan Prag, Nando de Freitas

Ithaca can attribute inscriptions to their original location with an accuracy of 71% and can date them to less than 30 years of their ground-truth ranges, redating key texts of Classical Athens and contributing to topical debates in ancient history.

Ancient Text Restoration Attribute

Interactive decoding of words from visual speech recognition models

no code implementations1 Jul 2021 Brendan Shillingford, Yannis Assael, Misha Denil

This work describes an interactive decoding method to improve the performance of visual speech recognition systems using user input to compensate for the inherent ambiguity of the task.

Position speech-recognition +1

Large-scale multilingual audio visual dubbing

no code implementations6 Nov 2020 Yi Yang, Brendan Shillingford, Yannis Assael, Miaosen Wang, Wendi Liu, Yutian Chen, Yu Zhang, Eren Sezener, Luis C. Cobo, Misha Denil, Yusuf Aytar, Nando de Freitas

The visual content is translated by synthesizing lip movements for the speaker to match the translated audio, creating a seamless audiovisual experience in the target language.

Translation

Recurrent Neural Network Transducer for Audio-Visual Speech Recognition

1 code implementation8 Nov 2019 Takaki Makino, Hank Liao, Yannis Assael, Brendan Shillingford, Basilio Garcia, Otavio Braga, Olivier Siohan

This work presents a large-scale audio-visual speech recognition system based on a recurrent neural network transducer (RNN-T) architecture.

Ranked #5 on Audio-Visual Speech Recognition on LRS3-TED (using extra training data)

Audio-Visual Speech Recognition Lipreading +2

Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations

1 code implementation ACL 2020 Oana-Maria Camburu, Brendan Shillingford, Pasquale Minervini, Thomas Lukasiewicz, Phil Blunsom

To increase trust in artificial intelligence systems, a promising research direction consists of designing neural models capable of generating natural language explanations for their predictions.

Decision Making Natural Language Inference

Speech bandwidth extension with WaveNet

no code implementations5 Jul 2019 Archit Gupta, Brendan Shillingford, Yannis Assael, Thomas C. Walters

This paper proposes an approach where a communication node can instead extend the bandwidth of a band-limited incoming speech signal that may have been passed through a low-rate codec.

Bandwidth Extension

Recovering Missing Characters in Old Hawaiian Writing

no code implementations EMNLP 2018 Brendan Shillingford, Oiwi Parker Jones

In contrast to the older writing system of the 19th century, modern Hawaiian orthography employs characters for long vowels and glottal stops.

Language Modelling Reading Comprehension +1

Large-Scale Visual Speech Recognition

no code implementations ICLR 2019 Brendan Shillingford, Yannis Assael, Matthew W. Hoffman, Thomas Paine, Cían Hughes, Utsav Prabhu, Hank Liao, Hasim Sak, Kanishka Rao, Lorrayne Bennett, Marie Mulville, Ben Coppin, Ben Laurie, Andrew Senior, Nando de Freitas

To achieve this, we constructed the largest existing visual speech recognition dataset, consisting of pairs of text and video clips of faces speaking (3, 886 hours of video).

Ranked #11 on Lipreading on LRS3-TED (using extra training data)

Lipreading speech-recognition +1

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