The Sociolinguistic Dimensions of Code-Switching between Arabic and English by Saudis

Ismail, Mahamod

doi:10.5539/ijel.v5n5p99

Cited by 9 publications

(10 citation statements)

References 12 publications

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“…Intra-sentential code switching is used when a speaker switches from one code to another using a phrase (Hoffman,1991;Ismail, 2015;Muysken, 2000). Such code switching often identified within Jun Bintang caption like in the following example.…”

Section: ) Intra-sentential Swicthingmentioning

confidence: 99%

Code Mixing and Switching on ‘Jun Bintang’ Captions on the Instagram

Larasati

Tantra

Utami

2021

jpbi

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The phenomenon of mixing and switching languages can easily be found both in real life and on social media, one of which is on Instagram. On Instagram, someone can express themselves in the Instagram caption as Jun Bintang did. Jun Bintang is a multilingual who uses Balinese, Indonesian and English as code mixing and code switching on Instagram social media. Investigating code mixing and code switching as found in the captions of Jun Bintang posts on his Instagram account was the sole research objective. Qualitative research design with descriptive method was applied on code mixing and code switching phenomena. The research objects were focused on Jun Bintang’s posts in three languages, they were, Balinese, Indonesian, and English. Data were collected through observations conducted in March to May,2020. Results of data analysis showed that code mixing types frequently used were such types like 1) insertion, 2) congruent lexicalization, and 3) alternation. Whilst, code switching types used were that of 1) inter-sentential, and 2) intra-sentential. Reasons for using code mixing and switching were identified as showing 1) empathy, 2) ease of using first language, 3) purpose of talking specific topic, 4) prestige, 5) interjection, 6) motive, and 7) group identity.

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Section: ) Intra-sentential Swicthingmentioning

confidence: 99%

Code Mixing and Switching on ‘Jun Bintang’ Captions on the Instagram

Larasati

Tantra

Utami

2021

jpbi

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“…The vast majority of the available CS speech corpora have covered Chinese-English [28,86,66,70,2], Hindi-English [34,82,87,90,78] and Spanish-English [88,33,82] language pairs. Less work has covered Arabic-English [54,46,47], Arabic-French [12,14], Frisian-Dutch [101], Mandarin-Taiwanese [69,68], Turkish-German [26], English-Malay [2], English-isiZulu [98] and Sepedi-English [73]. For Arabic CS, speech corpora are very limited in size as well as covered language-pairs.…”

Section: Cs Speech Corporamentioning

confidence: 99%

“…For Arabic CS, speech corpora are very limited in size as well as covered language-pairs. Ismail [54] collected an 89-minutes speech corpus by recording and transcribing informal dinner gatherings involving 6 participants. Amazouz et al [12] gathered a 7.5 hours of read speech from books and movie transcripts, as well as informal conversations, gathered from 20 speakers.…”

Section: Cs Speech Corporamentioning

confidence: 99%

Investigations on Speech Recognition Systems for Low-Resource Dialectal Arabic-English Code-Switching Speech

Hamed¹,

Denisov²,

Li³

et al. 2021

Preprint

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Code-switching (CS), defined as the mixing of languages in conversations, has become a worldwide phenomenon. The prevalence of CS has been recently met with a growing demand and interest to build CS ASR systems. In this paper, we present our work on code-switched Egyptian Arabic-English automatic speech recognition (ASR). We first contribute in filling the huge gap in resources by collecting, analyzing and publishing our spontaneous CS Egyptian Arabic-English speech corpus. We build our ASR systems using DNN-based hybrid and Transformer-based end-to-end models. In this paper, we present a thorough comparison between both approaches under the setting of a low-resource, orthographically unstandardized, and morphologically rich language pair. We show that while both systems give comparable overall recognition results, each system provides complementary sets of strength points. We show that recognition can be improved by combining the outputs of both systems. We propose several effective system combination approaches, where hypotheses of both systems are merged on sentence-and word-levels. Our approaches result in overall WER relative improvement of 4.7%, over a baseline performance of 32.1% WER. In the case of intra-sentential CS sentences, we achieve WER relative improvement of 4.8%. Our best performing system achieves 30.6% WER on ArzEn test set.

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“…Only two studies explored the linguistic gender-based differences among Saudi speakers. In one study, Ismail (2015) studied the frequency and types of code-switches from Arabic into English in young bilingual Saudis' casual conversations. She found that Saudi females code-switch more than males.…”

Section: Introductionmentioning

confidence: 99%

Linguistic Gender-Based Variations in Bani Buhair Dialect.

Alqarni¹

2019

Dialectologia

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The current article examines the linguistic gender-based variations between male and female speakers in Bani Buhair Dialect (BBD), a dialect spoken in the southwestern region of Saudi Arabia. It records, transcribes and investigates two natural conversations of two groups (two females and three males), each of which is one-hour-long. It explores the uses and frequencies of hedges, boosters, profanity, humor, interruptions and questions (common distinctive factors in language and gender studies). The results show that female participants use more hedges than male participants who use more boosters in comparison. As for humor and profanity, it has been observed that males produce more offensive words and show more sense of humor than females. With respect to interruptions and questions, the article shows that male participants interrupt and raise more questions during their conversation than their female counterparts.Keywords language, gender, Bani Buhair dialect VARIACIÓN LINGÜÍSTICA BASADA EN DIFERENCIAS DE GÉNERO EN EL DIALECTO DE BANI BUHAIR ResumenEste artículo examina las variaciones lingüísticas basadas en el género entre los hablantes masculinos y femeninos en el dialecto de Bani Buhair (BBD), hablado en la región suroeste de Arabia Saudita. Se registran, transcriben e investigan dos conversaciones espontáneas de dos grupos (dos mujeres y tres hombres), cada una de las cuales tiene una hora de duración. Se exploran los usos y las frecuencias de los atenuantes, refuerzos, blasfemias, humor, interrupciones y preguntas (factores distintivos comunes en los estudios de lenguaje y género). Los resultados muestran que las participantes femeninas usan más atenuantes que los participantes masculinos, los cuales usan más refuerzos desde un punto de vista comparativo. En cuanto al humor y la blasfemia, se ha observado que los hombres pronuncian palabras más ofensivas y muestran más sentido del humor que las mujeres. Con respecto a las interrupciones y las preguntas, el artículo muestra que los participantes masculinos interrumpen y plantean más preguntas durante su conversación que sus contrapartidas femeninas. Palabras clavelengua, género, dialecto Bani Buhair 1 Acknowledgement: The author would like to express his gratitude to King Khalid University (Saudi Arabia) for providing administrative and technical support.

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The Sociolinguistic Dimensions of Code-Switching between Arabic and English by Saudis

Cited by 9 publications

References 12 publications

Code Mixing and Switching on ‘Jun Bintang’ Captions on the Instagram

Code Mixing and Switching on ‘Jun Bintang’ Captions on the Instagram

Investigations on Speech Recognition Systems for Low-Resource Dialectal Arabic-English Code-Switching Speech

Linguistic Gender-Based Variations in Bani Buhair Dialect.

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