TY  - JOUR
T1  - Creating a of Noisy Environment Speech Mixture Dataset for Korean Speech Separation
AU  - Jang, Jaehoo 
AU  - Park, Kun 
AU  - Lee, Jeongpil 
AU  - Koo, Myoung-Wan 
JO  - Journal of KIISE, JOK
PY  - 2024
DA  - 2024/1/14
DO  - 10.5626/JOK.2024.51.6.513
KW  - noise data
KW  - overlapping sounds
KW  - speech overlap
KW  - speech separation
KW  - sound source separation
KW  - speech recognition
AB  - In the field of speech separation, models are typically trained using datasets that contain mixtures of speech and overlapping noise. Although there are established international datasets for advancing speech separation techniques, Korea currently lacks a similar precedent for constructing datasets with overlapping speech and noise. Therefore, this paper presents a dataset generator specifically designed for single-channel speech separation models tailored to the Korean language. The Korean Speech mixture with Noise dataset is introduced, which has been constructed using this generator. In our experiments, we train and evaluate a Conv-TasNet speech separation model using the newly created dataset. Additionally, we verify the dataset's efficacy by comparing the Character Error Rate (CER) between the separated speech and the original speech using a pre-trained speech recognition model.