Search Results for author: Jiyeon Kim

Found 5 papers, 0 papers with code

A comparison of streaming models and data augmentation methods for robust speech recognition

no code implementations19 Nov 2021 Jiyeon Kim, Mehul Kumar, Dhananjaya Gowda, Abhinav Garg, Chanwoo Kim

However, we observe that training of MoChA models seems to be more sensitive to various factors such as the characteristics of training sets and the incorporation of additional augmentations techniques.

Data Augmentation Robust Speech Recognition +1

Semi-supervised transfer learning for language expansion of end-to-end speech recognition models to low-resource languages

no code implementations19 Nov 2021 Jiyeon Kim, Mehul Kumar, Dhananjaya Gowda, Abhinav Garg, Chanwoo Kim

To improve the accuracy of a low-resource Italian ASR, we leverage a well-trained English model, unlabeled text corpus, and unlabeled audio corpus using transfer learning, TTS augmentation, and SSL respectively.

Data Augmentation speech-recognition +2

A review of on-device fully neural end-to-end automatic speech recognition algorithms

no code implementations14 Dec 2020 Chanwoo Kim, Dhananjaya Gowda, Dongsoo Lee, Jiyeon Kim, Ankur Kumar, Sungsoo Kim, Abhinav Garg, Changwoo Han

Conventional speech recognition systems comprise a large number of discrete components such as an acoustic model, a language model, a pronunciation model, a text-normalizer, an inverse-text normalizer, a decoder based on a Weighted Finite State Transducer (WFST), and so on.

Automatic Speech Recognition speech-recognition

end-to-end training of a large vocabulary end-to-end speech recognition system

no code implementations22 Dec 2019 Chanwoo Kim, Sungsoo Kim, Kwangyoun Kim, Mehul Kumar, Jiyeon Kim, Kyungmin Lee, Changwoo Han, Abhinav Garg, Eunhyang Kim, Minkyoo Shin, Shatrughan Singh, Larry Heck, Dhananjaya Gowda

Our end-to-end speech recognition system built using this training infrastructure showed a 2. 44 % WER on test-clean of the LibriSpeech test set after applying shallow fusion with a Transformer language model (LM).

Data Augmentation speech-recognition +1

Deep ensemble network with explicit complementary model for accuracy-balanced classification

no code implementations10 Aug 2019 Dohyun Kim, Kyeorye Lee, Jiyeon Kim, Junseok Kwon, Joongheon Kim

The average accuracy is one of major evaluation metrics for classification systems, while the accuracy deviation is another important performance metric used to evaluate various deep neural networks.

Classification General Classification

Cannot find the paper you are looking for? You can Submit a new open access paper.