Jinhwan Park

According to our database, Jinhwan Park authored at least 18 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

On the compression of shallow non-causal ASR models using knowledge distillation and tied-and-reduced decoder for low-latency on-device speech recognition.

Nagaraj Adiga, Jinhwan Park, Chintigari Shiva Kumar, Shatrughan Singh, Kyungmin Lee, Chanwoo Kim, Dhananjaya Gowda

CoRR, 2023

2022

Conformer-Based on-Device Streaming Speech Recognition with KD Compression and Two-Pass Architecture.

Jinhwan Park, Sichen Jin, Junmo Park, Sungsoo Kim, Dhairya Sandhyana, Changheon Lee, Myoungji Han, Jungin Lee, Seokyeong Jung, Changwoo Han, Chanwoo Kim

Proceedings of the IEEE Spoken Language Technology Workshop, 2022

Macro-Block Dropout for Improved Regularization in Training End-to-End Speech Recognition Models.

Chanwoo Kim, Sathish Indurti, Jinhwan Park, Wonyong Sung

Proceedings of the IEEE Spoken Language Technology Workshop, 2022

2021

Convolution-Based Attention Model With Positional Encoding For Streaming Speech Recognition On Embedded Devices.

Jinhwan Park, Chanwoo Kim, Wonyong Sung

Proceedings of the IEEE Spoken Language Technology Workshop, 2021

2020

S-SGD: Symmetrical Stochastic Gradient Descent with Weight Noise Injection for Reaching Flat Minima.

Wonyong Sung, Iksoo Choi, Jinhwan Park, Seokhyun Choi, Sungho Shin

CoRR, 2020

Effect of Adding Positional Information on Convolutional Neural Networks for End-to-End Speech Recognition.

Jinhwan Park, Wonyong Sung

Proceedings of the Interspeech 2020, 2020

Low-Latency Lightweight Streaming Speech Recognition with 8-Bit Quantized Simple Gated Convolutional Neural Networks.

Jinhwan Park, Xue Qian, Youngmin Jo, Wonyong Sung

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

HLHLp: Quantized Neural Networks Training for Reaching Flat Minima in Loss Surface.

Sungho Shin, Jinhwan Park, Yoonho Boo, Wonyong Sung

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Exploration of On-device End-to-End Acoustic Modeling with Neural Networks.

Wonyong Sung, Lukas Lee, Jinhwan Park

Proceedings of the 2019 IEEE International Workshop on Signal Processing Systems, 2019

Simple Gated Convnet for Small Footprint Acoustic Modeling.

Lukas Lee, Jinhwan Park, Wonyong Sung

Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2019

2018

Single Stream Parallelization of Recurrent Neural Networks for Low Power and Fast Inference.

Wonyong Sung, Jinhwan Park

CoRR, 2018

On-Device End-to-end Speech Recognition with Multi-Step Parallel Rnns.

Yoonho Boo, Jinhwan Park, Lukas Lee, Wonyong Sung

Proceedings of the 2018 IEEE Spoken Language Technology Workshop, 2018

Fully Neural Network Based Speech Recognition on Mobile and Embedded Devices.

Jinhwan Park, Yoonho Boo, Iksoo Choi, Sungho Shin, Wonyong Sung

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Hierarchical Recurrent Neural Networks for Acoustic Modeling.

Jinhwan Park, Iksoo Choi, Yoonho Boo, Wonyong Sung

Proceedings of the Interspeech 2018, 2018

Character-level Language Modeling with Gated Hierarchical Recurrent Neural Networks.

Iksoo Choi, Jinhwan Park, Wonyong Sung

Proceedings of the Interspeech 2018, 2018

2016

FPGA-Based Low-Power Speech Recognition with Recurrent Neural Networks.

Minjae Lee, Kyuyeon Hwang, Jinhwan Park, Sungwook Choi, Sungho Shin, Wonyong Sung

Proceedings of the 2016 IEEE International Workshop on Signal Processing Systems, 2016

Architecture exploration of a programmable neural network processor for embedded systems.

Wonyong Sung, Jinhwan Park

Proceedings of the International Conference on Embedded Computer Systems: Architectures, 2016

FPGA based implementation of deep neural networks using on-chip memory only.

Jinhwan Park, Wonyong Sung

Proceedings of the 2016 IEEE International Conference on Acoustics, 2016