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BanglaVoice: A curated sentence-level annotated dataset for active, passive, and middle voice in Bangla with baseline
Md Jahidul Alam1, Zannatul Mawa Koli2, Labony Sur2
1Department of Computer Science and Engineering, Chandpur Science and Technology University, Bangladesh.
Abstract:
BanglaVoice is a curated sentence-level dataset for grammatical voice analysis in Bangla, comprising 4397 annotated sentences categorized as Active (1459), Passive (1531), and Middle (1407). Each instance consists of a structurally complete clause containing a single dominant finite verb, accompanied by its English translation and a categorical voice label. Sentences were selectively compiled from publicly accessible Bangla digital sources published between 2023 and 2025 and underwent systematic cleaning, de-duplication, orthographic normalization, and UTF-8 standardization. Voice annotations were assigned using linguistically defined criteria and validated through multi-annotator agreement with majority voting. The dataset exhibits balanced class distribution and natural language characteristics, including a Zipfian rank-frequency distribution (s ≈ 0.98-0.99; R² ≈ 0.99) and substantial lexical diversity (3234 unique tokens). Baseline experiments using six supervised classifiers are also provided, with LinearSVC achieving 93.18% accuracy and 93.10% F1-score, establishing reproducible reference benchmarks for future Bangla grammatical voice classification research. BanglaVoice is released as an open-access resource to support morpho-syntactic research and voice-aware modelling in Bangla natural language processing.
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