Abstract
The paper applies a deep recurrent neural network to the task of sentence boundary detection in Sanskrit, an important, yet underresourced ancient Indian language. The deep learning approach improves the F scores set by a metrical baseline and by a Conditional Random Field classifier by more than 10%.