  We present KoSpeech, an open-source software, which is modular and extensible
end-to-end Korean automatic speech recognition (ASR) toolkit based on the deep
learning library PyTorch. Several automatic speech recognition open-source
toolkits have been released, but all of them deal with non-Korean languages,
such as English (e.g. ESPnet, Espresso). Although AI Hub opened 1,000 hours of
Korean speech corpus known as KsponSpeech, there is no established
preprocessing method and baseline model to compare model performances.
Therefore, we propose preprocessing methods for KsponSpeech corpus and a
baseline model for benchmarks. Our baseline model is based on Listen, Attend
and Spell (LAS) architecture and ables to customize various training
hyperparameters conveniently. By KoSpeech, we hope this could be a guideline
for those who research Korean speech recognition. Our baseline model achieved
10.31% character error rate (CER) at KsponSpeech corpus only with the acoustic
model. Our source code is available here.
