44 citations · 209 across the 16 of their papers we have counts for
16 papers
Asymmetric Proxy Loss for Multi-View Acoustic Word Embeddings
Myunghun Jung, Hoirin Kim
Acoustic word embeddings (AWEs) are discriminative representations of speech segments, and learned embedding space reflects the phonetic similarity between words. With multi-view l…
Supervised attention for speaker recognition
Seong Min Kye, Joon Son Chung, Hoirin Kim
The recently proposed self-attentive pooling (SAP) has shown good performance in several speaker recognition systems. In SAP systems, the context vector is trained end-to-end toget…
Learning to Maximize Speech Quality Directly Using MOS Prediction for Neural Text-to-Speech
Yeunju Choi, Youngmoon Jung, Youngjoo Suh +1
Although recent neural text-to-speech (TTS) systems have achieved high-quality speech synthesis, there are cases where a TTS system generates low-quality speech, mainly caused by l…
A Unified Deep Learning Framework for Short-Duration Speaker Verification in Adverse Environments
Youngmoon Jung, Yeunju Choi, Hyungjun Lim +1
Speaker verification (SV) has recently attracted considerable research interest due to the growing popularity of virtual assistants. At the same time, there is an increasing requir…
Deep MOS Predictor for Synthetic Speech Using Cluster-Based Modeling
Yeunju Choi, Youngmoon Jung, Hoirin Kim
While deep learning has made impressive progress in speech synthesis and voice conversion, the assessment of the synthesized speech is still carried out by human participants. Seve…
Dynamic Noise Embedding: Noise Aware Training and Adaptation for Speech Enhancement
Joohyung Lee, Youngmoon Jung, Myunghun Jung +1
Estimating noise information exactly is crucial for noise aware training in speech applications including speech enhancement (SE) which is our focus in this paper. To estimate nois…