Vietnamese, a low-resource language, is typically categorized into three primary dialect groups that belong to Northern, Central, and Southern Vietnam. However, each province within these regions exhibits its own distinct pronunciation variations. Despite the existence of various speech recognition datasets, none of them has provided a fine-grained classification of the 63 dialects specific to individual provinces of Vietnam. To address this gap, we introduce Vietnamese Multi-Dialect (ViMD) dataset, a novel comprehensive dataset capturing the rich diversity of 63 provincial dialects spoken across Vietnam. Our dataset comprises 102.56 hours of audio, consisting of approximately 19,000 utterances, and the associated transcripts contain over 1.2 million words. To provide benchmarks and simultaneously demonstrate the challenges of our dataset, we fine-tune state-of-the-art pre-trained models for two downstream tasks: (1) Dialect identification and (2) Speech recognition. The empirical results suggest two implications including the influence of geographical factors on dialects, and the constraints of current approaches in speech recognition tasks involving multi-dialect speech data. Our dataset is available for research purposes.

The child of a refugee from Vietnam is striving to realize her dream of building a Japanese language school in the Southeast Asian country. "My dream is to do something that would serve as a bridge between Japan and Vietnam," said Doan Thy Trang, 27. To achieve that goal, she founded a consulting firm in Akashi, a city in Hyogo Prefecture facing the Seto Inland Sea, in January 2015. Trang explained that many business trainees from Vietnam she meets through her work have little difficulty communicating with Japanese in daily conversations but struggle with technical terms. "Vietnamese need a school that teaches them Japanese language used in workplaces," she said.