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This study explores the practice of abalone fishing in the Wilayat of Sadah, located in the Dhofar Governorate in southernmost Oman. It draws on recent archaeological discoveries from Naatf Cave in the Hasik area, dating back to approximately 10,500 BCE, which revealed a variety of artifacts, including fishing tools, shells, and ornamental items that may be linked to abalone fishing. The research aims to explore the potential connections between these ancient finds and traditional abalone fishing practices by tracing patterns of continuity and transformation in the tools and customs associated with the activity up to the present day. It also sheds light on the socio-economic transformations of this profession in recent decades, particularly due to the rise in abalone prices and growing demand, which have fostered widespread community engagement and contributed to the development of new cultural practices. The study adopts a qualitative methodology, analyzing semi-structured interviews with local fishermen and reviewing relevant literature. The data were analyzed using MAXQDA software to extract the cultural and social meanings linked to abalone fishing. The findings indicate that some contemporary practices and tools continue to echo the symbolic or material characteristics of the ancient finds, reinforcing the hypothesis that abalone fishing is deeply rooted in the region’s coastal cultural heritage and not merely an economic activity. This study contributes valuable insights to archaeologists by offering a living cultural context through which ancient artifacts may be reinterpreted, thus bridging the deep past with the living present in the Omani maritime experience.
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Automatic Speech Recognition (ASR) has achieved strong performance in high-resource languages; however, Dialectal Arabic remains significantly under-resourced. This gap is particularly evident in Oman, where Arabic exhibits substantial sociolinguistic variation shaped by settlement patterns between sedentary (Hadari) and nomadic (Badu) communities, which are often overlooked by urbancentric or generalized Gulf Arabic datasets. We introduce OMAN-SPEECH, a sociolinguistically stratified spoken corpus for Omani Arabic comprising approximately 40 hours of spontaneous and semi-spontaneous speech from 32 speakers across 11 Wilayats (provinces). The corpus is balanced to capture regional and lifestyle variation and is annotated at the sentence level with Arabic transcription, English translation, and phonetic transcription using the International Phonetic Alphabet (IPA) through a human-in-the-loop annotation pipeline. OMAN-SPEECH provides a foundational resource for evaluating ASR and related speech technologies on Omani and Gulf Arabic varieties and supports more granular modeling of regional dialectal variation.
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