Thomas Hain


Uncertainty Aware Review Hallucination for Science Article Classification
Korbinian Friedl | Georgios Rizos | Lukas Stappen | Madina Hasan | Lucia Specia | Thomas Hain | Björn Schuller
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021


Using phone features to improve dialogue state tracking generalisation to unseen states
Iñigo Casanueva | Thomas Hain | Mauro Nicolao | Phil Green
Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue

The OpenCourseWare Metadiscourse (OCWMD) Corpus
Ghada Alharbi | Thomas Hain
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This study describes a new corpus of over 60,000 hand-annotated metadiscourse acts from 106 OpenCourseWare lectures, from two different disciplines: Physics and Economics. Metadiscourse is a set of linguistic expressions that signal different functions in the discourse. This type of language is hypothesised to be helpful in finding a structure in unstructured text, such as lectures discourse. A brief summary is provided about the annotation scheme and labelling procedures, inter-annotator reliability statistics, overall distributional statistics, a description of auxiliary data that will be distributed with the corpus, and information relating to how to obtain the data. The results provide a deeper understanding of lecture structure and confirm the reliable coding of metadiscursive acts in academic lectures across different disciplines. The next stage of our research will be to build a classification model to automate the tagging process, instead of manual annotation, which take time and efforts. This is in addition to the use of these tags as indicators of the higher level structure of lecture discourse.

A Framework for Collecting Realistic Recordings of Dysarthric Speech - the homeService Corpus
Mauro Nicolao | Heidi Christensen | Stuart Cunningham | Phil Green | Thomas Hain
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper introduces a new British English speech database, named the homeService corpus, which has been gathered as part of the homeService project. This project aims to help users with speech and motor disabilities to operate their home appliances using voice commands. The audio recorded during such interactions consists of realistic data of speakers with severe dysarthria. The majority of the homeService corpus is recorded in real home environments where voice control is often the normal means by which users interact with their devices. The collection of the corpus is motivated by the shortage of realistic dysarthric speech corpora available to the scientific community. Along with the details on how the data is organised and how it can be accessed, a brief description of the framework used to make the recordings is provided. Finally, the performance of the homeService automatic recogniser for dysarthric speech trained with single-speaker data from the corpus is provided as an initial baseline. Access to the homeService corpus is provided through the dedicated web page at This will also have the most updated description of the data. At the time of writing the collection process is still ongoing.


Knowledge transfer between speakers for personalised dialogue management
Iñigo Casanueva | Thomas Hain | Heidi Christensen | Ricard Marxer | Phil Green
Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue


The USFD SLT system for IWSLT 2014
Raymond W. M. Ng | Mortaza Doulaty | Rama Doddipatla | Wilker Aziz | Kashif Shah | Oscar Saz | Madina Hasan | Ghada AlHaribi | Lucia Specia | Thomas Hain
Proceedings of the 11th International Workshop on Spoken Language Translation: Evaluation Campaign

The University of Sheffield (USFD) participated in the International Workshop for Spoken Language Translation (IWSLT) in 2014. In this paper, we will introduce the USFD SLT system for IWSLT. Automatic speech recognition (ASR) is achieved by two multi-pass deep neural network systems with adaptation and rescoring techniques. Machine translation (MT) is achieved by a phrase-based system. The USFD primary system incorporates state-of-the-art ASR and MT techniques and gives a BLEU score of 23.45 and 14.75 on the English-to-French and English-to-German speech-to-text translation task with the IWSLT 2014 data. The USFD contrastive systems explore the integration of ASR and MT by using a quality estimation system to rescore the ASR outputs, optimising towards better translation. This gives a further 0.54 and 0.26 BLEU improvement respectively on the IWSLT 2012 and 2014 evaluation data.


homeService: Voice-enabled assistive technology in the home using cloud-based automatic speech recognition
Heidi Christensen | Iñigo Casanueva | Stuart Cunningham | Phil Green | Thomas Hain
Proceedings of the Fourth Workshop on Speech and Language Processing for Assistive Technologies


Impact du degré de supervision sur l’adaptation à un domaine d’un modèle de langage à partir du Web (Impact of the level of supervision on Web-based language model domain adaptation) [in French]
Gwénolé Lecorvé | John Dines | Thomas Hain | Petr Motlicek
Proceedings of the Joint Conference JEP-TALN-RECITAL 2012, volume 1: JEP