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dc.identifier.citationPadovani, I. (2020). Intelligent speech recognition data acquisition for Maltese (Bachelor's dissertation).en_GB
dc.description.abstractAutomatic Speech Recognition is a difficult task for under-resourced languages such as Maltese, as large quantities of data are required for its development. This dissertation seeks to provide a solution to this issue by crowdsourcing speech recordings and devising ways of validating this data efficiently. Common Voice was used as a crowdsourcing platform, facilitating the collection of 11+hours of speech data since its launch for Maltese. For validation, phonological analysis was performed on the text prompts using a grapheme-to-phoneme tool. The results of this were then compared to the number of syllables and segments detected in the speech using syllable nucleus detection and unsupervised automatic phoneme segmentation. Syllable distance between recordings and prompts was seen to be an effective metric for validation down to distances as small as a single syllable. Segment distance was effective when faced with differences of a few syllables or more.en_GB
dc.subjectSpeech processing systemsen_GB
dc.subjectAutomatic speech recognitionen_GB
dc.subjectMaltese languageen_GB
dc.titleIntelligent speech recognition data acquisition for Malteseen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.publisher.institutionUniversity of Maltaen_GB
dc.publisher.departmentInstitute of Linguistics and Language Technologyen_GB
dc.contributor.creatorPadovani, Ian-
Appears in Collections:Dissertations - InsLin - 2020

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