12 citations · 40 across the 18 of their papers we have counts for
16 papers · 1 filter
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…
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…
Extended U-Net for Speaker Verification in Noisy Environments
Ju-ho Kim, Jungwoo Heo, Hye-jin Shim +1
Background noise is a well-known factor that deteriorates the accuracy and reliability of speaker verification (SV) systems by blurring speech intelligibility. Various studies have…
RawNeXt: Speaker verification system for variable-duration utterances with deep layer aggregation and extended dynamic scaling policies
Ju-ho Kim, Hye-jin Shim, Jungwoo Heo +1
Despite achieving satisfactory performance in speaker verification using deep neural networks, variable-duration utterances remain a challenge that threatens the robustness of syst…
Learning Metrics from Mean Teacher: A Supervised Learning Method for Improving the Generalization of Speaker Verification System
Ju-ho Kim, Hye-jin Shim, Jee-weon Jung +1
Most speaker verification tasks are studied as an open-set evaluation scenario considering the real-world condition. Thus, the generalization power to unseen speakers is of paramou…
Capturing scattered discriminative information using a deep architecture in acoustic scene classification
Hye-jin Shim, Jee-weon Jung, Ju-ho Kim +1
Frequently misclassified pairs of classes that share many common acoustic properties exist in acoustic scene classification (ASC). To distinguish such pairs of classes, trivial det…
Integrated Replay Spoofing-aware Text-independent Speaker Verification
Hye-jin Shim, Jee-weon Jung, Ju-ho Kim +2
A number of studies have successfully developed speaker verification or presentation attack detection systems. However, studies integrating the two tasks remain in the preliminary…
Improved RawNet with Feature Map Scaling for Text-independent Speaker Verification using Raw Waveforms
Jee-weon Jung, Seung-bin Kim, Hye-jin Shim +2
Recent advances in deep learning have facilitated the design of speaker verification systems that directly input raw waveforms. For example, RawNet extracts speaker embeddings from…
Segment Aggregation for short utterances speaker verification using raw waveforms
Seung-bin Kim, Jee-weon Jung, Hye-jin Shim +2
Most studies on speaker verification systems focus on long-duration utterances, which are composed of sufficient phonetic information. However, the performances of these systems ar…
Acoustic Scene Classification using Audio Tagging
Jee-weon Jung, Hye-jin Shim, Ju-ho Kim +2
Acoustic scene classification systems using deep neural networks classify given recordings into pre-defined classes. In this study, we propose a novel scheme for acoustic scene cla…
RawNet: Advanced end-to-end deep neural network using raw waveforms for text-independent speaker verification
Jee-weon Jung, Hee-Soo Heo, Ju-ho Kim +2
Recently, direct modeling of raw waveforms using deep neural networks has been widely studied for a number of tasks in audio domains. In speaker verification, however, utilization…