activity
20192026
most citedWeakly Labeled Sound Event Detection Using Tri-training and Adversarial Learning

3 citations · 7 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

MoNe: Modular Neural Memory for Efficient Long Context Inference

Wonguk Cho, Kyubyung Chae, Tribhuvanesh Orekondy +6

We present MoNe, a lightweight modular neural memory that attaches to any frozen pretrained Transformer to enable long-context inference without retraining. MoNe reads context in f…

cs.CL2023

Knowledge Distillation from Non-streaming to Streaming ASR Encoder using Auxiliary Non-streaming Layer

Kyuhong Shim, Jinkyu Lee, Simyung Chang +1

Streaming automatic speech recognition (ASR) models are restricted from accessing future context, which results in worse performance compared to the non-streaming models. To improv…

cs.SD2021★ 1 cited

SubSpectral Normalization for Neural Audio Data Processing

Simyung Chang, Hyoungwoo Park, Janghoon Cho +3

Convolutional Neural Networks are widely used in various machine learning domains. In image processing, the features can be obtained by applying 2D convolution to all spatial dimen…

cs.SD2019★ 3 cited

Weakly Labeled Sound Event Detection Using Tri-training and Adversarial Learning

Hyoungwoo Park, Sungrack Yun, Jungyun Eum +2

This paper considers a semi-supervised learning framework for weakly labeled polyphonic sound event detection problems for the DCASE 2019 challenge's task4 by combining both the tr…

cs.SD2019★ 1 cited

Acoustic Scene Classification Based on a Large-margin Factorized CNN

Janghoon Cho, Sungrack Yun, Hyoungwoo Park +2

In this paper, we present an acoustic scene classification framework based on a large-margin factorized convolutional neural network (CNN). We adopt the factorized CNN to learn the…

cs.LG2019

Orthogonality Constrained Multi-Head Attention For Keyword Spotting

Mingu Lee, Jinkyu Lee, Hye Jin Jang +3

Multi-head attention mechanism is capable of learning various representations from sequential data while paying attention to different subsequences, e.g., word-pieces or syllables…

cs.LG2019★ 2 cited

Query-by-example on-device keyword spotting

Byeonggeun Kim, Mingu Lee, Jinkyu Lee +2

A keyword spotting (KWS) system determines the existence of, usually predefined, keyword in a continuous speech stream. This paper presents a query-by-example on-device KWS system…

eess.AS2019

An End-to-End Text-independent Speaker Verification Framework with a Keyword Adversarial Network

Sungrack Yun, Janghoon Cho, Jungyun Eum +2

This paper presents an end-to-end text-independent speaker verification framework by jointly considering the speaker embedding (SE) network and automatic speech recognition (ASR) n…