Hi, KIA: A Speech Emotion Recognition Dataset for Wake-Up Words

Wake-up word emotion recognition is a task to capture the speakers’ emotional state using short lexically-matched speech such as Ok Google or Hey Siri.

• Dataset & Pretrained Model at Zenodo

Reference

Hi, KIA: A Speech Emotion Recognition Dataset for Wake-Up Words [ArXiv]

@inproceedings{kim2022hi,
  title={Hi, KIA: A Speech Emotion Recognition Dataset for Wake-Up Words},
  author={Taesu Kim, SeungHeon Doh, Gyunpyo Lee, Hyung seok Jun, Juhan Nam, Hyeon-Jeong Suk},
  booktitle={Proceedings of the 14th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)},
  year={2022}
}

Requirements

1. Install python and PyTorch:

   • python==3.7
   • pytorch-lightning==1.4.9 (important!)
   • torch==1.7.1 (Please install it according to your CUDA version.)

2. Other requirements:

   • pip install -r requirements.txt

conda create -n YOUR_ENV_NAME python=3.7
conda activate YOUR_ENV_NAME
pip install -r requirements.txt

Training

1. Download the data files from HERE

2. Preprocessing audio: resampling to 16000

    python preprocessing.py
   

3. Transfer Learning training options:

    python train.py --freeze_type none
    python train.py --freeze_type feature # best option
    python train.py --freeze_type context
    python train.py --freeze_type all
   

Reproduce results in paper

Fore more examples, check bash files under scripts folder.

• you can check ML performance in notebook
• Reproduce performance in notebook

Inference using your own data (WIP)