Steve Cassidy

Case study

Publisher: Springer Netherlands

Date: 2017

DOI: 10.1007/978-94-024-0881-2_49

Two platforms for research in Human Communication Science: The AusTalk corpus and the Alveo Virtual Laboratory

Publisher: IEEE

Date: 09-2014

DOI: 10.1109/ICSDA.2014.7051412

Supporting accessibility and reproducibility in language research in the Alveo virtual laboratory

Publisher: Elsevier BV

Date: 09-2017

DOI: 10.1016/J.CSL.2017.01.003

DOM-based XHTML document structure analysis separating content from navigation elements

Publisher: IEEE

Date: 2005

DOI: 10.1109/CIMCA.2005.1631334

The mu + system for corpus based speech research

Publisher: Elsevier BV

Date: 10-1993

DOI: 10.1006/CSLA.1993.1017

Separating XHTML content from navigation clutter using DOM-structure block analysis

Publisher: ACM

Date: 06-09-2005

DOI: 10.1145/1083356.1083384

Multi-level annotation in the Emu speech database management system

Publisher: Elsevier BV

Date: 2001

DOI: 10.1016/S0167-6393(00)00069-8

The place of articulation distinction in voiced oral stops

Publisher: Walter de Gruyter GmbH

Date: 07-1995

DOI: 10.1159/000262182

Abstract: This study concerns the extent to which place of articulation in the voiced obstruents /b d dz g/ can be separated from spectral parameters taken in the burst, formant transitions, and a combination of the two. Classifications were obtained by training on citation-form data produced by male speakers and testing on (i) citation-form data produced by female speakers and (ii) continuous speech data produced by the same male speakers. The results show that there is more information for the place distinction in the burst than in formant transitions when the parameters are combined into a single model, classification scores are improved for the citation-form data, but not for the continuous speech data. The highest classification scores were in the vicinity of 90% correct for both types of data on the combined parameters. The results are seen as supporting a model of sufficient discriminability rather than one in which phonetic categories are characterised by invariant acoustic cues.

Updating the ICE annotation system: tagging, parsing and validation

Publisher: Edinburgh University Press

Date: 11-2011

DOI: 10.3366/COR.2011.0009

Abstract: The textual markup scheme of the International Corpus of English (ICE) project evolved continuously from 1988 on, more or less independently of the Text Encoding Initiative (TEI). It was intended to standardise the annotation of all the regional ICE corpora, in order to facilitate comparisons of their linguistic content. However, this goal has proved elusive because of gradual changes in the ICE annotation system, and additions to it made by those working on in idual ICE corpora. Furthermore, since the project pre-dates the development of XML-based markup standards, the format of the ICE markup does not match that in many modern corpora and can be difficult to manipulate. As a goal of the original project was interoperability of the various ICE corpora, it is important that the markup of existing and new ICE corpora can be converted into a common format that can serve their ongoing needs, while allowing older markup to be fully included. This paper describes the most significant variations in annotation, and focusses on several points of difficulty that are inherent in the system – especially the non-hierarchical treatment of the visual and structural elements of written texts, and of overlapping speech in spontaneous conversation. We report on our development of a parser to validate the existing ICE markup scheme and convert it to other formats. The development of this tool brings the Australian version into line with the current ICE standard, and also allows for proper validation of all annotation in any of the regional corpora. Once the corpora have been validated, they can be converted easily to a standardised XML format for alternative systems of corpus annotation, such as that developed by the TEI.

Querying databases of annotated speech

Publisher: IEEE Comput. Soc

Date: 2000

DOI: 10.1109/ADC.2000.819808

Tools for multimodal annotation

Publisher: Springer Netherlands

Date: 2017

DOI: 10.1007/978-94-024-0881-2_7

Designing annotation schemes

Publisher: Springer Netherlands

Date: 2017

DOI: 10.1007/978-94-024-0881-2_3

FAIRer Data through Digital Recording: The FAIMS Mobile Experience

Publisher: Ubiquity Press, Ltd.

Date: 10-11-2022

DOI: 10.5334/JCAA.96

Techniques in speech acoustics

Publisher: Springer Netherlands

Date: 1999

DOI: 10.1007/978-94-011-4657-9

Dynamic and Target Theories of Vowel Classification

Publisher: SAGE Publications

Date: 10-1994

DOI: 10.1177/002383099403700402

Abstract: Recent studies on the perception of speech have suggested that vowel identification depends on dynamic cues, rather than a single ‘static’ spectral slice at the vowel midpoint. The experiments reported in this paper seek both to test the extent to which vowel recognition depends on dynamic information, and to identify the nature of the dynamic cues on which such recognition might depend. Gaussian classification techniques, as well as different kinds of neural network architectures, were used to classify some 3000 vowels in /CVd/ citation-form Australian English words, following training on roughly the same number of vowel tokens produced by different talkers. The first set of experiments shows that when vowels are classified from three spectral slices taken at the vowel margins and midpoint, only diphthongs, but not monophthongs, benefit from the additional spectral information at the vowel margins. A further experiment shows that vowels are no better classified from a time-delay neural network than from the three-slice network in which time is not explicitly represented. At least for the citation-form, Australian English vowels in this study, these results are interpreted as being more consistent with a target, rather than a dynamic, theory of vowel perception.

Macquarie University

Location: Australia

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Linkage Projects - Grant ID: LP190100900

Start Date: 11-2020

End Date: 11-2024

Amount: $150,000.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP0776267

Start Date: 07-2007

End Date: 12-2012

Amount: $230,643.00

Funder: Australian Research Council

Special Research Initiatives - Grant ID: SR0567319

Start Date: 10-2005

End Date: 08-2007

Amount: $145,000.00

Funder: Australian Research Council

Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100211

Start Date: 07-2010

End Date: 06-2015

Amount: $650,000.00

Funder: Australian Research Council