no code implementations • CoNLL (EMNLP) 2021 • Emma O’Neill, Joe Kenny, Anthony Ventresque, Julie Carson-Berndsen
A child who is unfamiliar with the correct spelling of a word often employs a “sound it out” approach: breaking the word down into its constituent sounds and then choosing letters to represent the identified sounds.
no code implementations • NAACL (SIGMORPHON) 2022 • Patrick Cormac English, John D. Kelleher, Julie Carson-Berndsen
In recent years large transformer model architectures have become available which provide a novel means of generating high-quality vector representations of speech audio.
no code implementations • 19 Jul 2023 • Long Mai, Julie Carson-Berndsen
The integration of natural language processing (NLP) technologies into educational applications has shown promising results, particularly in the language learning domain.
no code implementations • 12 May 2023 • Emma O'Neill, Julie Carson-Berndsen
A deeper understanding of the behaviour of an ASR system is thus beneficial from a speech technology standpoint, in terms of improving ASR accuracy, and from an annotation standpoint, where knowing the likely errors made by an ASR system can aid in this manual correction.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 24 Sep 2022 • Long Mai, Julie Carson-Berndsen
The transcription quality of automatic speech recognition (ASR) systems degrades significantly when transcribing audios coming from unseen domains.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • LREC 2012 • Amalia Zahra, Julie Carson-Berndsen
The work presented in this paper explores the use of Indonesian transliteration to support English pronunciation practice.
no code implementations • LREC 2012 • Joao Paulo Cabral, Mark Kane, Zeeshan Ahmed, Mohamed Abou-Zleikha, {\'E}va Sz{\'e}kely, Amalia Zahra, Kalu Ogbureke, Peter Cahill, Julie Carson-Berndsen, Stephan Schl{\"o}gl
An experiment was conducted in this work that combines the MySpeech service with the WebWOZ Wizard-of-Oz platform (http://www. webwoz. com), in order to improve the human-computer interaction (HCI) of the service and the feedback that it provides to the user.
no code implementations • LREC 2012 • {\'E}va Sz{\'e}kely, Joao Paulo Cabral, Mohamed Abou-Zleikha, Peter Cahill, Julie Carson-Berndsen
In our previous research we have shown that it is possible to detect different expressive voice styles represented in a particular audiobook, using unsupervised clustering to group the speech corpus of the audiobook into smaller subsets representing the detected voice styles.