Landmark-based analysis of speech differentiates conversational from clear speech in speakers with muscle tension dysphonia (2023)

Keiko Ishikaw, Mary Pietrowicz, Sara Charney, Diana Orbelo
This study evaluated the feasibility of differentiating conversational and clear speech produced by individuals with muscle tension dysphonia (MTD) using landmark-based analysis of speech (LMBAS). Thirty-four adult speakers with MTD recorded conversational and clear speech, with 27 of them able to produce clear speech. The recordings of these individuals were analyzed with the open-source LMBAS program, SpeechMark®, MATLAB Toolbox version 1.1.2. The results indicated that glottal landmarks, burst onset landmarks, and the duration between glottal landmarks differentiated conversational speech from clear speech. LMBAS shows potential as an approach for detecting the difference between conversational and clear speech in dysphonic individuals.

Copyright (2023) Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America.

The article appeared in JASA Express Letters 3, 055203 (2023) and may be found at the following link:

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Landmark-based approach for automatically describing the effect of spasmodic dysphonia on speech production: Preliminary case studies

Keiko Ishikawaa and Joel MacAuslan

Abstract: Spasmodic dysphonia causes voice breaks in linguistically inappropriate places in speech. Landmark-based analysis automatically describes this speech segmentation error.

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Copyright (2019) This article may be downloaded for personal use only. Any other use requires prior permission of the author.


Toward clinical application of landmark-based speech analysis: Landmark expression in normal adult speech

Keiko Ishikawaa, Joel MacAuslan, Suzanne Boyce

Abstract: The goal of clinical speech analysis is to describe abnormalities in speech production that affect a speaker’s intelligibility. Landmark analysis identifies abrupt changes in a speech signal and classifies them according to their acoustic profiles. These acoustic markers, called landmarks, may help describe intelligibility deficits in disordered speech. As a first step toward clinical application of landmark analysis, the present study describes expression of landmarks in normal speech. Results of the study revealed that syllabic, glottal, and burst landmarks consist of 94% of all landmarks, and suggest the effect of gender needs to be considered for the analysis.

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Copyright (2017) Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America.

The following article appeared in The Journal of the Acoustical Society of America 142, EL441 (2017) and may be found at

Application of Laryngeal Landmarks for Characterization of Dysphonic Speech (2017)

Keiko Ishikawa, Joel MacAuslan, Suzanne Boyce
People don’t understand me in noisy places” is one of the most commonly reported concerns among individuals with dysphonia. Dysphonia is often a result of laryngeal pathology, which elicits greater aperiodicity and instability in a speech signal. These acoustic abnormalities likely contribute to the intelligibility deficit reported by these individuals.

Acoustic analysis is commonly used in dysphonia evaluation. Multiple algorithms are available for characterizing the degree of aperiodicity in speech. Typically, the degree of aperiodicity is measured over a particular length of voicing or speech selected by a user. While such algorithms are effective for describing degree of dysphonic voice quality perceived by listeners, an algorithm that describes timing and frequency of aperiodic moments may provide information more relevant to intelligibility.

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Predicting Intelligibility of Dysphonic Speech with Automatic Measurement of Vowel Related Parameters (2017)

Keiko Ishikawa, Meredith Meyer, Joel MacAuslan, Suzanne Boyce

• Reduced intelligibility is a common complaint among people with dysphonia.

• Vowels carry information that greatly contributes to intelligibility.

• A formant is a cluster of frequencies amplified by the vocal tract. The first two formants are critical for perception of vowels.

• A greater amount of noise and a lack of harmonic power are common characteristics of dysphonic speech signals. These acoustic abnormalities can negatively affect perceptual resolution of formants.

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Automated Analysis of Syllable Complexity as an Indicator of Speech Disorder (2017)

Marisha Speights, Joel MacAuslan, Noah Silbert, Suzanne Boyce
This study was designed to examine the feasibility of the Syllabic Cluster algorithm in the SpeechMark® MATLAB toolbox as an automated approach for identifying differences in speakers with and without Speech Sound Disorders(SSD).


  • In the course of normal development, children master voluntary coordination of the motoric movements necessary for the utterance of complex syllables.
  • Development of well-formed syllables has been shown to be a significant predictor of later communication skills.
  • Children with delayed speech production show atypical trends in the mastery of well-formed syllables, especially in continuous speech.

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Automated Screening for Speech Disorders Using Acoustic Landmark Detection (2017)

Marisha Speights, Keiko Ishikawa, Joel MacAuslan, Suzanne Boyce
The purpose of this study is to characterize differences in the speech of children with and without speech disorders by using an automated acoustic landmark based approach.
This pilot study explores entropy as a tool for characterizing differences in the landmark (LM) acoustic sequence between normal adults and children with and without a Speech Sound Disorder (SSD). Shannon’s Entropy and ROC analysis are used to evaluate the landmark patterns as potential diagnostic measures of atypical speech production. We discuss these results and our future work toward developing a fully automated clinical screening tool.

Introduction: Speech Disorders in Children

  • Speech requires precision in 1) planning and execution of articulatory targets and 2) sequencing the timing, direction, and force of the articulators. Speech is susceptible to decreased accuracy and precision due to the complexity of such movements 1,2
  • Most children effortlessly learn how to coordinate movements for normal speech production.2-5
  • About one in twelve preschool-aged children, however, show delays in speech production capability that may put them at risk for academic and behavioral difficulties, if not identified and treated.6

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What Are Acoustic Landmarks, and What Do They Describe?

In speech acoustics, landmarks are patterns that mark certain speech-production events. Speechacoustic
landmarks come in two classes: peak and abrupt.

Peak: At present, the peak landmarks detected in SpeechMark® are vowel landmarks (VLMs) and
frication landmarks. These are identified as instants in an utterance at which a maximum (or peak) of
harmonic power or of fractal dimension occurs, respectively, and may be considered the centers of
the vowels or fricated intervals (resp.).

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Peak Landmarks in SpeechMark

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. Here we describe the peak
set of landmarks used in SpeechMark®.

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Spectrogram SNR and Spectrogram Displays

We are often presented with a waveform or spectrogram for which it is helpful to suppress details in noise-dominated sections of time (in the waveform) or of time-frequency(“T-F”, in the spectrogram).

In keeping with the knowledge-based focus of SpeechMark, we are particularly interested in solutions based on broad principles rather than ones that must be determined in a subtle, complicated, or ad hoc fashion, whether by the user or by SpeechMark.

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