CLUTTERING SEVERITY ASSESSMENT: TALKING TIME DETERMINATION DURING ORAL READING

Similar documents
Treating Cluttered Speech in a Child with Autism: Case Study

Feedback and feedforward control in apraxia of speech: Noise masking effects on fricative production.

SCRIPT FOR PODCAST ON DIGITAL HEARING AIDS STEPHANIE COLANGELO AND SARA RUSSO

TWO CHANNEL CLINICAL AUDIOMETER AUDIOSTAR PRO

Noise-Robust Speech Recognition Technologies in Mobile Environments

Advanced Audio Interface for Phonetic Speech. Recognition in a High Noise Environment

HearIntelligence by HANSATON. Intelligent hearing means natural hearing.

Shaheen N. Awan 1, Nancy Pearl Solomon 2, Leah B. Helou 3, & Alexander Stojadinovic 2

**Do not cite without authors permission** Beliefs and attitudes of children and adults who stutter regarding their ability to overcome stuttering

Evaluating Auditory Contexts and Their Impacts on Hearing Aid Outcomes with Mobile Phones

Speech Recognition. Setup Guide for Win 7. Debbie Hebert, PT, ATP Central AT Services

ACOUSTIC ANALYSIS AND PERCEPTION OF CANTONESE VOWELS PRODUCED BY PROFOUNDLY HEARING IMPAIRED ADOLESCENTS

OIML R 122 Annex C RECOMMENDATION. Edition 1999 (E) ORGANISATION INTERNATIONALE INTERNATIONAL ORGANIZATION

noise induced Working Together to Prevent Hearing Loss

Reality Audiology: Insights from the pediatric real world

User Guide V: 3.0, August 2017

Roger TM. Learning without limits. SoundField for education

Four-Channel WDRC Compression with Dynamic Contrast Detection

Language Volunteer Guide

AA-M1C1. Audiometer. Space saving is achieved with a width of about 350 mm. Audiogram can be printed by built-in printer

The Camperdown Program for Stuttering: Treatment Manual. Sue O Brian, Brenda Carey, Mark Onslow, Ann Packman and Angela Cream.

DSM PRO. Software Training Manual. Copyright November 2003

MedRx HLS Plus. An Instructional Guide to operating the Hearing Loss Simulator and Master Hearing Aid. Hearing Loss Simulator

===================================================================

The Effect of Analysis Methods and Input Signal Characteristics on Hearing Aid Measurements

Speech Spectra and Spectrograms

ASU Speech and Hearing Clinic Spring Testing. Adult Speech and Language Evaluation

C H A N N E L S A N D B A N D S A C T I V E N O I S E C O N T R O L 2

Walkthrough

Interact-AS. Use handwriting, typing and/or speech input. The most recently spoken phrase is shown in the top box

Audioconference Fixed Parameters. Audioconference Variables. Measurement Method: Physiological. Measurement Methods: PQ. Experimental Conditions

Effects of speaker's and listener's environments on speech intelligibili annoyance. Author(s)Kubo, Rieko; Morikawa, Daisuke; Akag

Critical Review: Using Video Modelling to Teach Verbal Social Communication Skills to Children with Autism Spectrum Disorder

Errol Davis Director of Research and Development Sound Linked Data Inc. Erik Arisholm Lead Engineer Sound Linked Data Inc.

MEASUREMENTS AND EQUIPMENT FOR AUDIOLOGICAL EVALUATIONS

Hearing Corrector Version 1.1. Hearing Corrector. Software package: Version 1.1, This documentation:

Step-by-Step RECD Guide

Critical Review: Are laryngeal manual therapies effective in improving voice outcomes of patients with muscle tension dysphonia?

Critical Review: Does Delayed Auditory Feedback Improve Speech Intelligibility in Parkinson s Disease?

How to use AutoFit (IMC2) How to use AutoFit (IMC2)

Initial - AR. Learning Objectives: Using This Lesson Effectively: CompleteSpeech

Attitude Towards Tobacco Use

CST for Windows. Version 1.0 Revised: 7/29/13. Software to administer and score the Connected Speech Test (CST)

The Effects of Sleep Deprivation on the Acoustic and Perceptual Characteristics of Voice

Sophia Neppel M.Cl.Sc (SLP) Candidate University of Western Ontario: School of Communication Sciences and Disorders

Acoustic Correlates of Speech Naturalness in Post- Treatment Adults Who Stutter: Role of Fundamental Frequency

ECG MACHINE KEC- Series

R: Initial - Pr. Learning Objectives:

AUTISM SPECTRUM RATING SCALES (ASRS )

Quick Guide Binaural REM

Use of Auditory Techniques Checklists As Formative Tools: from Practicum to Student Teaching

Effects of Setting Thresholds for the MED- EL Cochlear Implant System in Children

Audioconference Fixed Parameters. Audioconference Variables. Measurement Method: Perceptual Quality. Measurement Method: Physiological

ACOUSTIC MOMENTS DATA

EFFECTS OF RHYTHM ON THE PERCEPTION OF URGENCY AND IRRITATION IN 1 AUDITORY SIGNALS. Utrecht University

IDENTIFYING THE AUTHORITATIVE JUDGMENTS OF STUTTERING: COMPARISONS OF SELF-JUDGMENTS AND OBSERVER JUDGMENTS

User Manual Verizon Wireless. All Rights Reserved. verizonwireless.com OM2260VW

How to Use Own Voice Processing in Connexx 8. Rebecca Herbig, AuD

Solutions for better hearing. audifon innovative, creative, inspired

TOWN OF FAIRFIELD PUBLIC HEALTH NURSING. MANUAL: School Health APPROVED BY: Board of Health School Medical Advisor

A SYSTEM FOR CONTROL AND EVALUATION OF ACOUSTIC STARTLE RESPONSES OF ANIMALS

LENA Project. Listen and Talk Early Intervention Program & Fontbonne University Deaf Education Program Collaboration 2016

Debsubhra Chakraborty Institute for Media Innovation, Interdisciplinary Graduate School Nanyang Technological University, Singapore

Sonic Spotlight. Binaural Coordination: Making the Connection

SANAKO Lab 100 STS USER GUIDE

New CTA PSAP Quality Standard (Starting with Some Interesting Questions)

Items pertaining to drunk driving

Effects of noise and filtering on the intelligibility of speech produced during simultaneous communication

AT235/AT235h Middle Ear Analyzers. Diagnostic & clinical tympanometry with basic audiometry.

Electro-Acoustic Stimulation (EAS) Naída CI Q90 EAS System. Naída CI Q90 EAS System Components. Naída CI Q90 Acoustic Earhook

An algorithm modelling the Irrelevant Sound Effect (ISE)

AEROWIN RT: CLINCAL APPLICATION

The Impact of Presentation Level on SCAN A Test Performance

SUPPORTING TERTIARY STUDENTS WITH HEARING IMPAIRMENT

TOPICS IN AMPLIFICATION

Restaurant Survey Results (as of 6/3/11)

AudioSense: Enabling Real-time Evaluation of Hearing Aid Technology In-Situ

Critical Review: The Effects of Self-Imposed Time-Out from Speaking on Stuttering in Adolescents and Adults Who Stutter

MEMO. Authorization to Purchase Acoustic Panel Material Operations Building

Unit III Verbal and Non-verbal Communication

Initial. Learning Objectives: Using This Lesson Effectively: CompleteSpeech

Oral Presentation #6 Clinical Analysis of Speech Rhythms in Language Development using MATLAB

Visi-Pitch IV is the latest version of the most widely

Assistive Technologies

2012, Greenwood, L.

Analysis of the Audio Home Environment of Children with Normal vs. Impaired Hearing

When a biometric hearing aid gives you access to better hearing performance, life is on

Thrive Hearing Control Application

How to use mycontrol App 2.0. Rebecca Herbig, AuD

INTRODUCTION J. Acoust. Soc. Am. 103 (2), February /98/103(2)/1080/5/$ Acoustical Society of America 1080

GSI TYMPSTAR PRO CLINICAL MIDDLE-EAR ANALYZER. Setting The Clinical Standard

ACCESSIBILITY FOR THE DISABLED

Production of Stop Consonants by Children with Cochlear Implants & Children with Normal Hearing. Danielle Revai University of Wisconsin - Madison

Automated and Standardized Counting of Mouse Bone Marrow CFU Assays

Voice production. M Södersten, Karolinska Institutet, Rekjavik, Oct 12, Larynx and the vocal folds. Structure of a vocal fold

CLASSROOM AMPLIFICATION: WHO CARES? AND WHY SHOULD WE? James Blair and Jeffery Larsen Utah State University ASHA, San Diego, 2011

How to use mycontrol App 2.0. Rebecca Herbig, AuD

Biomedical Instrumentation E. Blood Pressure

ipod Noise Exposure Assessment in Simulated Environmental Conditions

Transcription:

CLUTTERING SEVERITY ASSESSMENT: TALKING TIME DETERMINATION DURING ORAL READING Klaas Bakker Su Jin Lee Missouri State University, Springfield, MO Florence Myers Lawrence Raphael Adelphi University, Garden City, NY Ken St. Louis West Virginia University, Morgantown, WV Percentage talking time cluttered has been recently suggested as a procedure for expressing cluttering severity (Bakker, St. Louis, Myers & Raphael, 2005). It captures the proportion of talking time during which cluttering is observed by a clinician. The currently available procedure (Bakker et al., 2005) involves simultaneous determination of talking time and cluttering time while a speaking sample is in progress. The need to determine talking and cluttering time in real-time is a challenge. Also, the procedure has not been completely tested. Only one aspect, a clinician s ability to determine talking time, has been researched so far. Although reasonable levels of reliability had been previously established (Bakker & Lawson, 2006), the researched procedures were either time consuming (acoustic workstation) or cumbersome (when determined realtime manually). Therefore a new method was developed that determines acoustic talking time automatically (Bakker, 2007). Initial research with this method demonstrated high levels of intra- and inter-rater reliability, accuracy, and concurrent validity when used on digitally recorded monologues. PURPOSE The present study was conducted to further determine the respective levels of reliability, accuracy, and validity of the aforementioned three procedures for talking time determination. Specifically, it was to: (1). replicate the earlier findings obtained on recorded monologues

(Bakker, 2007), and (2). evaluate the generalizability of the earlier findings to other speaking conditions (specifically, oral reading).

METHOD Eleven adult normal speakers orally read the Rainbow Passage. Speech was digitally recorded in a sound treated booth (using a KayPentax Visipitch IV; 22,050Hz sampling rate; 16 bits; saved as *.wav files). The participants were instructed to read the passage out loud in their own usual way. Talking time was determined following three measurement protocols: (1). Using an acoustic workstation (PRAAT, see Figure1 and Note 1). Pauses (silences >=200ms) and non-speech sounds (e. g., sounds associated with speech breathing) were manually removed from the recordings by visually inspecting (and replaying if necessary) the associated intensity envelopes. Figure 1. PRAAT screen showing a selected pause. (2). Using a manual real-time procedure (Cluttering Assessment Program/CLASP 3.0; see below and Note 2).

Figure 2. Typical screen of CLASP 3.0 following a talking time recording session. (3). Using a custom made software program (Bakker, 2007) to determine talking time (semi-) automatically (See Figure 3). That is, after a user selects three intervals of silence (assumed to be representative for background noise), the software calculates a cut-off level for determining when speech is or is not present. After this talking time is computed, or the time during which a signal exceeds the cut-off criterion and does not return below it for more than 200ms. Figure 3. Screen showing a representative pause selection in preparation for an automated talking time determination.

RESULTS Each procedure for measuring talking time duration was accomplished with high levels of intra- and inter-rate reliability. Table 1 shows the reliability coefficients that were obtained: Table 1. Intra- and inter-rater reliability coefficients for three talking time measurement procedures Intra-rater Inter-rater Reliability Reliability Workstation (PRAAT):.990.983 Manual real-time (CLASP 3.0):.994.986 Computer-semi automatic:.997.994 The following table shows the means (in seconds) that were obtained: Table 2. Means of talking times (in seconds) determined twice by one user and once by a second user. Deleted: User 1 User 1 User 2 First Second First Workstation: 26.16 26.13 26.86 Manual real-time: 24.93 25.08 25.60 Computer: 26.15 26.17 26.34 The means reflect that the workstation and computer-automated procedures produced the most consistent results and were highly similar in an absolute

sense. The manual real time values overall were about a second shorter than either computer-based result. If the workstation-based procedure (about 20-25 minutes per sample!) can be considered the gold standard, the computer-automatic procedure (about 20 seconds) promises to be a highly desirable clinical procedure. The manual online scoring procedure remains an attractive, though somewhat cumbersome, alternate for the workstationbased procedure as well. As the workstation-based the talking time determination procedure can be considered gold standard for measuring talking time, it could serve as a basis for assessing the concurrent validity of the other newer procedures that were investigated. The concurrent validity for using the real-time manual procedure, or the CLASP 3.0 software (rxy=.972, df=9) and the custom designed automated talking time procedure (rxy =.979, df=9) are very high. These results provide support that the procedures are interchangeable. Considering all it makes the automated procedure the most attractive one as it takes the least amount of time to administer. CONCLUSION Future development of a cluttering severity assessment system that depends on talking time determination benefits most from using the computerautomated strategy for talking time estimation. Results of the present study support the use of computer-assisted methods for estimation of talking time, as the basis for further development of a computer-assisted cluttering severity assessment system. These methods were found to be time-efficient, reliable and valid. NOTES Note 1. PRAAT: Doing phonetics by computer (Boersma and Weenink). Freeware software program available through www.praat.org Note 2. CLASP 3.0: Cluttering Assessment Program, custom-made by first author. It contains a procedure for determining talking time through manually, employing a highly accurate and reliable timing strategy. REFERENCES Bakker, K. (May, 2007). Objectifying measures of cluttered speech. First World Conference on Cluttering, Katarino, Bulgaria.

Bakker, K., & Lawson, S. (2006). Manual measurement of talking time: Reliability, validity and accuracy. Annual National Convention of the American Speech Language and Hearing Association, Miami Beach, FL. Bakker, K., St. Louis, K. O., Myers, F., & Raphael, L. (2005). A freeware software tool for determining aspects of cluttering severity. Annual National Convention of the American Speech Language and Hearing Association, San Diego, CA.