Spoken Language Identification Using Deep Learning

Bachelor Thesis Project

A Deep Learning-Based Approach for Spoken Language Identification

Dataset

• Kaggle's spoken language identification with 73080 samples from English, Spanish, and German languages.
• ShEMO a large-scale validated database for Persian speech emotion detection

Feature Extraction

Mel Spectrogram is used for feature extraction and results are saved into .npy files. The model reads them using a custom data generator.

Architecture

This project implemented two different architectures CNN and CRNN.

Website

There is also a website!

Presentation video

You can watch presentation in Persian Here.