Research Tools for Speech
Landmarks (LMs) are acoustically identifiable points in an utterance. They come in the form of abrupt transitions (abrupt LMs) and peaks (peak LMs) of some contour or contours.
Until now the only peak type has been Vowel, computed by vowel_lms.
For vowels the peak is that of maximum harmonic power and often corresponds to the maximum opening of the mouth.
Frication-type peak landmarks are computed using…
The SpeechMark MATLAB Toolbox is a platform-independent add-in to the MATLAB language and computation environment, developed by MathWorks. This Toolbox adds acoustic landmark detection and visualization tools, methods, and scripts to MATLAB.
Downloading
This product is a standard MATLAB toolbox. To use it, a valid instance of MATLAB (version R2010b or newer) must be installed, as well as a valid version of the MATLAB Signal Processing Toolbox.
Karen Chenausky, Joel MacAuslan, and Richard Goldhor
Parkinson’s disease (PD) is an idiopathic neurodegenerative disease caused by loss of dopamineproducing cells in the substantia nigra of the basal ganglia, affecting over one-half million people in the U.S., most over age 50. Its major symptoms are muscular rigidity, bradykinesia, resting tremor, and postural instability. An estimated 70%–90% of patients with PD also develop speech or voice disorders…
Speights, Marisha, and Boyce, Suzanne and MacAuslan, Joel and Fell, Harriet,
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.
Voiced interval was greater in dysphonic speech – more frequent instance of unexpected vocal fold onset and offset occurred in unexpected moments. Other parameters for syllabic cluster measure were not significant predictors for dysphonic speech.
The analysis may have been affected by the wide variability seen in dysphonic group (especially VF paralysis group).
the LMs are placed at instants of abrupt change of energy occurring simultaneously across multiple frequency ranges and at multiple time scales.
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.
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.
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.
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.
SpeechMark Advisor Program
The SpeechMark development team is looking for researchers and teachers to provide feedback that will help us improve SpeechMark.
If you fit this description, we invite you to become a key part of the SpeechMark development process by applying to become a SpeechMark Advisor.
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