Multiclass Language Identification using Deep Learning on Spectral Images of Audio Signals

Understand

The first step in any voice recognition software is to determine what language a speaker is using, and ideally this process would be automated.

• The technique described in this paper, language identification for audio spectrograms (LIFAS), uses spectrograms generated from audio signals as inputs to a convolutional neural network (CNN) to be used for language identification.
• LIFAS requires minimal pre-processing on the audio signals as the spectrograms are generated during each batch as they are input to the network during training.
• LIFAS utilizes deep learning tools that are shown to be successful on image processing tasks and applies it to audio signal classification.