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India has twenty-two official languages. Serving such a diverse language baseis a challenge for survey statisticians, call center operators, softwaredevelopers, and other such service providers. To help provide better servicesto different language communities via better localization, we introduce a newmachine learning model that predicts the language(s) that the user can speakfrom their name. Using nearly 438M records spanning 33 Indian states and 1.13Munique last names from the Indian Electoral Rolls Corpus (?), we build acharacter-level transformer-based machine-learning model that predicts thestate of residence based on the last name. The model has a top-3 accuracy of85.3% on unseen names. We map the states to languages using the Indian censusto infer languages understood by the respondent. We provide open-sourcesoftware that implements the method discussed in the paper.

Instate: Predicting the State of Residence From Last Name