APSIPA-TER

This code is the implementation of Text Emotion Recognition (TER) with linguistic features.
The network model is BERT with a pretrained model parameter.

How to use

  1. Edit txt2tsv.py and preprocess your files
python3 txt2tsv.py
  1. Edit hyper_param.yaml
  2. Run main.py
python3 main.py

Reference

[1] GitHub_cl-tohoku/bert-japanese, https://github.com/cl-tohoku/bert-japanese (Last View: 2022-02-07)

[2] Huggingface_bert-japanese, https://huggingface.co/docs/transformers/model_doc/bert-japanese (Last View: 2022-02-07)

[3] Qiita-自然言語処理モデル（BERT）を利用した日本語の文章分類, https://qiita.com/takubb/items/fd972f0ac3dba909c293 (Last View: 2022-02-07)

Paper

Ryotaro Nagase, Takahiro Fukumori and Yoichi Yamashita: “Speech Emotion Recognition with Fusion of Acoustic- and Linguistic-Feature-Based Decisions, ” Proc. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), pp. 725 — 730, 2021.