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 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. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.