SpeechMark Publications and Presentations

Automatic Syllabic Cluster Analysis of Children’s Speech Data to Identify Speech-Disorders

This research investigates syllabic complexity in children with normal and disordered speech production using a computerized method of analysis.

Automatic Syllabic Cluster Analysis based upon landmark theory (Stevens 1992, 2002; Liu 1996; Howitt 2000; Fell & MacAuslan, 2005) is used to automate the analysis of child speech.

The algorithm automatically measures acoustic changes that correspond to syllable patterns and provides a fast method for measuring complexity in syllable production without the need for phonetic transcription.

Measurement of child speech complexity using acoustic landmark detection
Speights, Marisha and Boyce, Suzanne and MacAuslan, Joel and Fell, Harriet, The Journal of the Acoustical Society of America, 137, 2301-2301 (2015), DOI:http://dx.doi.org/10.1121/1.4920400

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Poster from the SpeechMark exhibit at the Acoustical Society of America Meeting, April 2014

the LMs are placed at instants of abrupt change of energy occurring simultaneously across multiple frequency ranges and at multiple time scales.

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SpeechMark Acoustic Landmark Tool: Application to Voice Pathology

Suzanne Boyce; Marisha Speights; Keiko Ishikawa; Joel MacAuslan

One area of voice research that has historically been understudied is the interaction between voice pathology and acoustic aspects of the speech signal that affect intelligibility. Landmark-based software tools are particularly suited to fast, automatic analysis of small, non-lexical differences in the acoustic signal reflecting the production of speech. We are building a tool set that provides fast, automatic summary statistics for measures of speech acoustics based on Stevens’ paradigm of landmarks, points in an utterance around which information about articulatory events can be extracted. This paper explores the use of landmark analysis for evaluation of intelligibility-based measures of vocal pathology. Index Terms: speech analysis, landmarks, voice pathology.

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SpeechMark: Landmark Detection Tool for Speech Analysis

Suzanne Boyce; Harriet Fell; Joel MacAuslan

Landmark-based software tools are particularly suited to fast, automatic analysis of small, non-lexical differences in production of the same speech material by the same speaker. We are building a suite of independent applications and plugins as toolkits that make our landmark-based software system, SpeechMark, available to the wider scientific community. This will be achieved by extending existing software platforms with “plug-ins” that perform specific measures and report results to the user and by developing a MATLAB toolkit. These tools provide automatic summary statistics for measures of speech acoustics based on Stevens’ paradigm of landmarks, points in an utterance around which information about articulatory events can be extracted.

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Automated Tools for Identifying Syllabic Landmark Clusters that Reflect Changes in Articulation

Suzanne Boyce; Harriet Fell; Lorin Wilde; Joel MacAuslan

We have developed a set of software tools to detect articulatory changes in the production of syllabic units based on acoustic landmark detection and classification. Results from the application of this automatic analysis system to studies of Parkinson’s Disease and Sleep Deprivation show the ability to detect subtle change. We are making these tools available as add-ons to systems such as Wavesurfer and R.

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A Platform for Automated Acoustic Analysis for Assistive Technology

Suzanne Boyce; Harriet Fell; Joel MacAuslan; Lorin Wilde
The use of speech production data has been limited by a steep learning curve and the need for laborious hand measurement. We are building a tool set that provides summary statistics for measures designed by clinicians to screen, diagnose or provide training to assistive technology users. This will be achieved by extending an existing shareware software platform with “plug-ins” that perform specific measures and report results to the user. The common underlying basis for this tool set is a Stevens’ paradigm of landmarks, points in an utterance around which information about articulatory events can be extracted.

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