9 citations · 13 across the 5 of their papers we have counts for
5 papers
Data-driven grapheme-to-phoneme representations for a lexicon-free text-to-speech
Abhinav Garg, Jiyeon Kim, Sushil Khyalia +2
Grapheme-to-Phoneme (G2P) is an essential first step in any modern, high-quality Text-to-Speech (TTS) system. Most of the current G2P systems rely on carefully hand-crafted lexicon…
Semi-supervised transfer learning for language expansion of end-to-end speech recognition models to low-resource languages
Jiyeon Kim, Mehul Kumar, Dhananjaya Gowda +2
In this paper, we propose a three-stage training methodology to improve the speech recognition accuracy of low-resource languages. We explore and propose an effective combination o…
A comparison of streaming models and data augmentation methods for robust speech recognition
Jiyeon Kim, Mehul Kumar, Dhananjaya Gowda +2
In this paper, we present a comparative study on the robustness of two different online streaming speech recognition models: Monotonic Chunkwise Attention (MoChA) and Recurrent Neu…
A review of on-device fully neural end-to-end automatic speech recognition algorithms
Chanwoo Kim, Dhananjaya Gowda, Dongsoo Lee +5
In this paper, we review various end-to-end automatic speech recognition algorithms and their optimization techniques for on-device applications. Conventional speech recognition sy…
end-to-end training of a large vocabulary end-to-end speech recognition system
Chanwoo Kim, Sungsoo Kim, Kwangyoun Kim +10
In this paper, we present an end-to-end training framework for building state-of-the-art end-to-end speech recognition systems. Our training system utilizes a cluster of Central Pr…