Word recognition testing may be defined as a procedure to assess a listener’s ability to identify one-syllable words (such as phonetically-balanced/PB words) that are presented at a given suprathreshold level to arrive at a word recognition score. For Thai, Thammasat University and Ramathibodi Hospital Phonetically Balanced Word Lists 2015 (TU-RAMA PB’15) were created with five lists, each with 25 monosyllabic words. Besides its phoneme distributions being based on large-scale Thai spoken corpora, TU-RAMA PB’15 is in line with TU PB’14 with emphasis on phonetic balance, symmetrical phoneme occurrence, and word familiarity. To evaluate its homogeneity in terms of decibel intelligibility, the lists were recorded and presented to 10 normal hearing participants, ranging from 0 to 50 dB HL in 2 dB increments (ascending order) until they repeated correct verbal responses. Using logistic regression, regression slopes and intercepts were calculated to estimate percentage of correct performance at any given intensity and to construct psychometric functions for every list. Derived psychometric function slopes ranged from 0.2015 to 0.2262 while intensities required for 50% intelligibility ranged from 17.0876 to 20.8856. Two-way Chi-Square analysis performed on both parameters indicated that there was no significant difference among the five lists.
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2 November 2015
170th Meeting of the Acoustical Society of America
02–06 November 2015
Jacksonville, Florida
Psychological and Physiological Acoustics: Paper 3aPP8
Article Contents
June 26 2017
Phonetically balanced and psychometrically equivalent monosyllabic word lists for word recognition testing in Thai Free
Sajeerat Poonyaban;
Sajeerat Poonyaban
1Center of Excellence in Intelligent Informatics, Speech and Language Technology, and Service Innovation (CILS),
Thammasat University
, Thailand
;2Department of Electrical and Computer Engineering, Faculty of Engineering,
Thammasat University
, Rangsit Campus, Khlong Luang, Pathum Thani, Thailand
; [email protected]; [email protected]; [email protected]; [email protected]
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Pasinee Aungsakulchai;
Pasinee Aungsakulchai
1Center of Excellence in Intelligent Informatics, Speech and Language Technology, and Service Innovation (CILS),
Thammasat University
, Thailand
;2Department of Electrical and Computer Engineering, Faculty of Engineering,
Thammasat University
, Rangsit Campus, Khlong Luang, Pathum Thani, Thailand
; [email protected]; [email protected]; [email protected]; [email protected]
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Charturong Tantibundhit;
Charturong Tantibundhit
1Center of Excellence in Intelligent Informatics, Speech and Language Technology, and Service Innovation (CILS),
Thammasat University
, Thailand
;2Department of Electrical and Computer Engineering, Faculty of Engineering,
Thammasat University
, Rangsit Campus, Khlong Luang, Pathum Thani, Thailand
; [email protected]; [email protected]; [email protected]; [email protected]
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Chutamanee Onsuwan;
Chutamanee Onsuwan
1Center of Excellence in Intelligent Informatics, Speech and Language Technology, and Service Innovation (CILS),
Thammasat University
, Thailand
;3Department of English and Linguistics, Faculty of Liberral Arts,
Thammasat University
, Rangsit Campus, Khlong Luang, Pathum Thani, Thailand
; [email protected]
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Rattinan Tiravanitchakul;
Rattinan Tiravanitchakul
4Department of Communication Science and Disorders, Faculty of Medicine,
Mahidol University
, Thailand
; [email protected]
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Krit Kosawat;
Krit Kosawat
5NECTEC,
National Science and Technology Development Agency (NSTDA)
, Pathum Thani, Thailand
; [email protected]
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Adirek Munthuli
Adirek Munthuli
1Center of Excellence in Intelligent Informatics, Speech and Language Technology, and Service Innovation (CILS),
Thammasat University
, Thailand
;2Department of Electrical and Computer Engineering, Faculty of Engineering,
Thammasat University
, Rangsit Campus, Khlong Luang, Pathum Thani, Thailand
; [email protected]; [email protected]; [email protected]; [email protected]
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Sajeerat Poonyaban
1,2
Pasinee Aungsakulchai
1,2
Charturong Tantibundhit
1,2
Chutamanee Onsuwan
1,3
Rattinan Tiravanitchakul
4
Krit Kosawat
5
Adirek Munthuli
1,2
1
Center of Excellence in Intelligent Informatics, Speech and Language Technology, and Service Innovation (CILS),
Thammasat University
, Thailand
;
2
Department of Electrical and Computer Engineering, Faculty of Engineering,
Thammasat University
, Rangsit Campus, Khlong Luang, Pathum Thani, Thailand
; [email protected]; [email protected]; [email protected]; [email protected]
3
Department of English and Linguistics, Faculty of Liberral Arts,
Thammasat University
, Rangsit Campus, Khlong Luang, Pathum Thani, Thailand
; [email protected]
4
Department of Communication Science and Disorders, Faculty of Medicine,
Mahidol University
, Thailand
; [email protected]
5
NECTEC,
National Science and Technology Development Agency (NSTDA)
, Pathum Thani, Thailand
; [email protected]Proc. Mtgs. Acoust. 25, 050003 (2015)
Article history
Received:
February 13 2017
Accepted:
April 26 2017
Citation
Sajeerat Poonyaban, Pasinee Aungsakulchai, Charturong Tantibundhit, Chutamanee Onsuwan, Rattinan Tiravanitchakul, Krit Kosawat, Adirek Munthuli; Phonetically balanced and psychometrically equivalent monosyllabic word lists for word recognition testing in Thai. Proc. Mtgs. Acoust. 2 November 2015; 25 (1): 050003. https://doi.org/10.1121/2.0000496
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