  This memo describes NTR-TSU submission for SIGTYP 2021 Shared Task on
predicting language IDs from speech.
  Spoken Language Identification (LID) is an important step in a multilingual
Automated Speech Recognition (ASR) system pipeline. For many low-resource and
endangered languages, only single-speaker recordings may be available,
demanding a need for domain and speaker-invariant language ID systems. In this
memo, we show that a convolutional neural network with a Self-Attentive Pooling
layer shows promising results for the language identification task.
