Helpful Neighbors: Leveraging Neighbors in Geographic Feature Pronunciation
This work addresses pronunciation prediction for place names, which is an incremental improvement with applications in mapping services and linguistics.
The paper tackles the problem of predicting geographic feature pronunciations by leveraging neighboring names' pronunciations, demonstrating its utility in correcting errors in Google Maps for Japanese place names and applying it to cognate reflex prediction in linguistics.
If one sees the place name Houston Mercer Dog Run in New York, how does one know how to pronounce it? Assuming one knows that Houston in New York is pronounced "how-ston" and not like the Texas city, then one can probably guess that "how-ston" is also used in the name of the dog park. We present a novel architecture that learns to use the pronunciations of neighboring names in order to guess the pronunciation of a given target feature. Applied to Japanese place names, we demonstrate the utility of the model to finding and proposing corrections for errors in Google Maps. To demonstrate the utility of this approach to structurally similar problems, we also report on an application to a totally different task: Cognate reflex prediction in comparative historical linguistics. A version of the code has been open-sourced (https://github.com/google-research/google-research/tree/master/cognate_inpaint_neighbors).