  India has twenty-two official languages. Serving such a diverse language base
is a challenge for survey statisticians, call center operators, software
developers, and other such service providers. To help provide better services
to different language communities via better localization, we introduce a new
machine learning model that predicts the language(s) that the user can speak
from their name. Using nearly 438M records spanning 33 Indian states and 1.13M
unique last names from the Indian Electoral Rolls Corpus (?), we build a
character-level transformer-based machine-learning model that predicts the
state of residence based on the last name. The model has a top-3 accuracy of
85.3% on unseen names. We map the states to languages using the Indian census
to infer languages understood by the respondent. We provide open-source
software that implements the method discussed in the paper.

Computer Vision and Pattern Recognition