Skip to content

Latest commit

 

History

History
20 lines (12 loc) · 605 Bytes

readme.md

File metadata and controls

20 lines (12 loc) · 605 Bytes

Multimodal speech emotion recognition Using Audio and Text

Project for HSE Deep Learning course: emotions recognition from audio and text.

Dataset

IEMOCAMP dataset with 4 largest emotion classes and united class "happy" and "excited". Preprocessed and splitted into train, test, validation as 8:1:1.

Models architectures

Model

  • ARE model: CNN

baseline/baseline_audio.py

  • TRE model: GRU

baseline/baseline_text.py