An Experiment on Lexical Stress in Pakistani English Speech
The study aims to investigate acoustic patterns of word stress in Pakistani English (PE) speech. It hypothesizes that lexical stress in Pakistani English modifies acoustic properties and that speakers of English do not differentiate disyllabic words as nouns or verbs based on lexical stress in Engli...
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| Veröffentlicht in: | Corpus pragmatics : international journal of corpus linguistics and pragmatics Jg. 9; H. 1; S. 75 - 103 |
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| Sprache: | Englisch |
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01.03.2025
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| Abstract | The study aims to investigate acoustic patterns of word stress in Pakistani English (PE) speech. It hypothesizes that lexical stress in Pakistani English modifies acoustic properties and that speakers of English do not differentiate disyllabic words as nouns or verbs based on lexical stress in English. The study offers valuable insights into the variability of English speech among Pakistani L1 speakers, contributing to the understanding of English pronunciation in a multilingual context; particularly focusing on the pronunciation differences among speakers with various first languages (L1), including Sindhi, Urdu, Punjabi, Pashto, and Balochi. By examining the acoustic properties such as pitch (F0), duration, and vowel formants (F1 and F2), the study is committed to identifying and comparing the lexical stress patterns in (PE), using a sample of 100 (20 for each language) participants from different L1 backgrounds. Seven pairs of disyllabic words were selected as stimuli following the methodology of as reported (Beckman Stress and non-stress accent, Foris Publications, 1986). and (Fry in Journal of the Acoustical Society of America 27:765–768, 1955), (Fry in Language and Speech 1:120–152, 1958). Each word pair consisted of a noun and a verb that had identical spelling forms and differed only in terms of stress placement (noun: stress on the initial syllable; verb: stress on the final syllable). These stimulus pairs were formed from the following corpus of word forms:
contract
,
desert
,
object
,
permit
,
rebel
,
record
, and
subject
. Each target word was elicited in isolation and in the semantically neutral frame sentence
I said
__
this time
and accompanied by associated context sentences created specifically for each word. The study's experimental data sets will be used to train machine learning models, which will increase the accuracy of voice recognition for English speakers in Pakistan. For linguistic study and pedagogical reasons, the study offers insights into the phonetic variants of Pakistani English. The study's conclusions can help develop speech recognition and machine learning tools that more accurately understands and interprets the lexical stress patterns in Pakistani English speech. |
|---|---|
| AbstractList | The study aims to investigate acoustic patterns of word stress in Pakistani English (PE) speech. It hypothesizes that lexical stress in Pakistani English modifies acoustic properties and that speakers of English do not differentiate disyllabic words as nouns or verbs based on lexical stress in English. The study offers valuable insights into the variability of English speech among Pakistani L1 speakers, contributing to the understanding of English pronunciation in a multilingual context; particularly focusing on the pronunciation differences among speakers with various first languages (L1), including Sindhi, Urdu, Punjabi, Pashto, and Balochi. By examining the acoustic properties such as pitch (F0), duration, and vowel formants (F1 and F2), the study is committed to identifying and comparing the lexical stress patterns in (PE), using a sample of 100 (20 for each language) participants from different L1 backgrounds. Seven pairs of disyllabic words were selected as stimuli following the methodology of as reported (Beckman Stress and non-stress accent, Foris Publications, 1986). and (Fry in Journal of the Acoustical Society of America 27:765–768, 1955), (Fry in Language and Speech 1:120–152, 1958). Each word pair consisted of a noun and a verb that had identical spelling forms and differed only in terms of stress placement (noun: stress on the initial syllable; verb: stress on the final syllable). These stimulus pairs were formed from the following corpus of word forms:
contract
,
desert
,
object
,
permit
,
rebel
,
record
, and
subject
. Each target word was elicited in isolation and in the semantically neutral frame sentence
I said
__
this time
and accompanied by associated context sentences created specifically for each word. The study's experimental data sets will be used to train machine learning models, which will increase the accuracy of voice recognition for English speakers in Pakistan. For linguistic study and pedagogical reasons, the study offers insights into the phonetic variants of Pakistani English. The study's conclusions can help develop speech recognition and machine learning tools that more accurately understands and interprets the lexical stress patterns in Pakistani English speech. |
| Author | Khosh, Neda Kameh Shaikh, Imtiaz Husain Bakhsh, Illahi Abbasi, Abdul Malik |
| Author_xml | – sequence: 1 givenname: Abdul Malik orcidid: 0000-0002-0481-2992 surname: Abbasi fullname: Abbasi, Abdul Malik email: amabbasi@smiu.edu.pk organization: Faculty of Language and Culture Studies, Sindh Madressatul Islam University – sequence: 2 givenname: Imtiaz Husain surname: Shaikh fullname: Shaikh, Imtiaz Husain organization: Department of Artificial Intelligence and Mathematical Sciences, Sindh Madressatul Islam University – sequence: 3 givenname: Illahi surname: Bakhsh fullname: Bakhsh, Illahi organization: Institute of Language and Literature, University of Sindh – sequence: 4 givenname: Neda Kameh surname: Khosh fullname: Khosh, Neda Kameh organization: Peoples’ Friendship University of Russia, Named after Patrice Lumumba |
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| Cites_doi | 10.1086/422264 10.1017/S0025100300002061 10.1016/0024-3841(89)90038-7 10.1121/1.1908022 10.1044/jslhr.4105.1042 10.1109/ICSLP.1996.607440 10.5539/ijel.v8n4p115 10.59670/ml.v21is4.7247 10.1121/1.2902165 10.1017/S095267579700331X 10.1121/1.1918816 10.5539/ijel.v8n5p27 10.1016/B0-08-044854-2/02241-0 10.1007/s10772-024-10122-8 10.1017/S095267570000066X 10.21437/ICSLP.1992-272 10.1515/9783111354873 10.1007/s10772-024-10162-0 10.1515/9783110874020 10.1017/9780511807954 10.5539/ijel.v8n2p92 10.1016/0388-0001(91)90009-P 10.1016/j.specom.2024.103174 10.5539/ijel.v8n3p101 10.1017/S0952675700000403 |
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| Keywords | Lexical stress Pakistani English Algorithm Accent Speech recognition Machine learning |
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