2 citations · 6 across the 9 of their papers we have counts for
9 papers
SV-Mixer: Replacing the Transformer Encoder with Lightweight MLPs for Self-Supervised Model Compression in Speaker Verification
Jungwoo Heo, Hyun-seo Shin, Chan-yeong Lim +4
Self-supervised learning (SSL) has pushed speaker verification accuracy close to state-of-the-art levels, but the Transformer backbones used in most SSL encoders hinder on-device a…
MR-RawNet: Speaker verification system with multiple temporal resolutions for variable duration utterances using raw waveforms
Seung-bin Kim, Chan-yeong Lim, Jungwoo Heo +4
In speaker verification systems, the utilization of short utterances presents a persistent challenge, leading to performance degradation primarily due to insufficient phonetic info…
HM-Conformer: A Conformer-based audio deepfake detection system with hierarchical pooling and multi-level classification token aggregation methods
Hyun-seo Shin, Jungwoo Heo, Ju-ho Kim +3
Audio deepfake detection (ADD) is the task of detecting spoofing attacks generated by text-to-speech or voice conversion systems. Spoofing evidence, which helps to distinguish betw…
Diff-SV: A Unified Hierarchical Framework for Noise-Robust Speaker Verification Using Score-Based Diffusion Probabilistic Models
Ju-ho Kim, Jungwoo Heo, Hyun-seo Shin +2
Background noise considerably reduces the accuracy and reliability of speaker verification (SV) systems. These challenges can be addressed using a speech enhancement system as a fr…
PAS: Partial Additive Speech Data Augmentation Method for Noise Robust Speaker Verification
Wonbin Kim, Hyun-seo Shin, Ju-ho Kim +3
Background noise reduces speech intelligibility and quality, making speaker verification (SV) in noisy environments a challenging task. To improve the noise robustness of SV system…
One-Step Knowledge Distillation and Fine-Tuning in Using Large Pre-Trained Self-Supervised Learning Models for Speaker Verification
Jungwoo Heo, Chan-yeong Lim, Ju-ho Kim +2
The application of speech self-supervised learning (SSL) models has achieved remarkable performance in speaker verification (SV). However, there is a computational cost hurdle in e…
Convolution channel separation and frequency sub-bands aggregation for music genre classification
Jungwoo Heo, Hyun-seo Shin, Ju-ho Kim +2
In music, short-term features such as pitch and tempo constitute long-term semantic features such as melody and narrative. A music genre classification (MGC) system should be able…
Integrated Parameter-Efficient Tuning for General-Purpose Audio Models
Ju-ho Kim, Jungwoo Heo, Hyun-seo Shin +2
The advent of hyper-scale and general-purpose pre-trained models is shifting the paradigm of building task-specific models for target tasks. In the field of audio research, task-ag…
Two Methods for Spoofing-Aware Speaker Verification: Multi-Layer Perceptron Score Fusion Model and Integrated Embedding Projector
Jungwoo Heo, Ju-ho Kim, Hyun-seo Shin
The use of deep neural networks (DNN) has dramatically elevated the performance of automatic speaker verification (ASV) over the last decade. However, ASV systems can be easily neu…