Search Results for author: Sangjun Park

Found 5 papers, 2 papers with code

Into-TTS : Intonation Template Based Prosody Control System

no code implementations4 Apr 2022 JIhwan Lee, Joun Yeop Lee, Heejin Choi, Seongkyu Mun, Sangjun Park, Jae-Sung Bae, Chanwoo Kim

Two proposed modules are added to the end-to-end TTS framework: an intonation predictor and an intonation encoder.

Language Modelling

Bunched LPCNet2: Efficient Neural Vocoders Covering Devices from Cloud to Edge

no code implementations27 Mar 2022 Sangjun Park, Kihyun Choo, Joohyung Lee, Anton V. Porov, Konstantin Osipov, June Sig Sung

Text-to-Speech (TTS) services that run on edge devices have many advantages compared to cloud TTS, e. g., latency and privacy issues.

Computational Efficiency

Ethereum ECCPoW

1 code implementation26 Jan 2021 Hyoungsung Kim, Jehyuk Jang, Sangjun Park, Heung-No Lee

A finite mean block generation time (BGT) and none heavy-tail BGT distribution are the ones of the focus in this study.

Cryptography and Security

Bunched LPCNet : Vocoder for Low-cost Neural Text-To-Speech Systems

no code implementations11 Aug 2020 Ravichander Vipperla, Sangjun Park, Kihyun Choo, Samin Ishtiaq, Kyoungbo Min, Sourav Bhattacharya, Abhinav Mehrotra, Alberto Gil C. P. Ramos, Nicholas D. Lane

LPCNet is an efficient vocoder that combines linear prediction and deep neural network modules to keep the computational complexity low.

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