399 citations · 430 across the 15 of their papers we have counts for
16 papers
Latent Filling: Latent Space Data Augmentation for Zero-shot Speech Synthesis
Jae-Sung Bae, Joun Yeop Lee, Ji-Hyun Lee +4
Previous works in zero-shot text-to-speech (ZS-TTS) have attempted to enhance its systems by enlarging the training data through crowd-sourcing or augmenting existing speech data.…
An Empirical Study on L2 Accents of Cross-lingual Text-to-Speech Systems via Vowel Space
Jihwan Lee, Jae-Sung Bae, Seongkyu Mun +4
With the recent developments in cross-lingual Text-to-Speech (TTS) systems, L2 (second-language, or foreign) accent problems arise. Moreover, running a subjective evaluation for su…
Into-TTS : Intonation Template Based Prosody Control System
Jihwan Lee, Joun Yeop Lee, Heejin Choi +4
Intonations play an important role in delivering the intention of a speaker. However, current end-to-end TTS systems often fail to model proper intonations. To alleviate this probl…
Streaming end-to-end speech recognition with jointly trained neural feature enhancement
Chanwoo Kim, Abhinav Garg, Dhananjaya Gowda +2
In this paper, we present a streaming end-to-end speech recognition model based on Monotonic Chunkwise Attention (MoCha) jointly trained with enhancement layers. Even though the Mo…
Overcoming label noise in audio event detection using sequential labeling
Jae-Bin Kim, Seongkyu Mun, Myungwoo Oh +3
This paper addresses the noisy label issue in audio event detection (AED) by refining strong labels as sequential labels with inaccurate timestamps removed. In AED, strong labels c…
Metric Learning for Keyword Spotting
Jaesung Huh, Minjae Lee, Heesoo Heo +2
The goal of this work is to train effective representations for keyword spotting via metric learning. Most existing works address keyword spotting as a closed-set classification pr…
In defence of metric learning for speaker recognition
Joon Son Chung, Jaesung Huh, Seongkyu Mun +7
The objective of this paper is 'open-set' speaker recognition of unseen speakers, where ideal embeddings should be able to condense information into a compact utterance-level repre…
The sound of my voice: speaker representation loss for target voice separation
Seongkyu Mun, Soyeon Choe, Jaesung Huh +1
Content and style representations have been widely studied in the field of style transfer. In this paper, we propose a new loss function using speaker content representation for au…
Delving into VoxCeleb: environment invariant speaker recognition
Joon Son Chung, Jaesung Huh, Seongkyu Mun
Research in speaker recognition has recently seen significant progress due to the application of neural network models and the availability of new large-scale datasets. There has b…
Domain Mismatch Robust Acoustic Scene Classification using Channel Information Conversion
Seongkyu Mun, Suwon Shon
In a recent acoustic scene classification (ASC) research field, training and test device channel mismatch have become an issue for the real world implementation. To address the iss…
Analysis Acoustic Features for Acoustic Scene Classification and Score fusion of multi-classification systems applied to DCASE 2016 challenge
Sangwook Park, Seongkyu Mun, Younglo Lee +2
This paper describes an acoustic scene classification method which achieved the 4th ranking result in the IEEE AASP challenge of Detection and Classification of Acoustic Scenes and…
Recursive Whitening Transformation for Speaker Recognition on Language Mismatched Condition
Suwon Shon, Seongkyu Mun, Hanseok Ko
Recently in speaker recognition, performance degradation due to the channel domain mismatched condition has been actively addressed. However, the mismatches arising from language i…
Autoencoder based Domain Adaptation for Speaker Recognition under Insufficient Channel Information
Suwon Shon, Seongkyu Mun, Wooil Kim +1
In real-life conditions, mismatch between development and test domain degrades speaker recognition performance. To solve the issue, many researchers explored domain adaptation appr…
DNN Transfer Learning based Non-linear Feature Extraction for Acoustic Event Classification
Seongkyu Mun, Minkyu Shin, Suwon Shon +3
Recent acoustic event classification research has focused on training suitable filters to represent acoustic events. However, due to limited availability of target event databases…
Non-negative matrix factorization-based subband decomposition for acoustic source localization
Suwon Shon, Seongkyu Mun, David Han +1
A novel non-negative matrix factorization (NMF) based subband decomposition in frequency spatial domain for acoustic source localization using a microphone array is introduced. The…
KU-ISPL Language Recognition System for NIST 2015 i-Vector Machine Learning Challenge
Suwon Shon, Seongkyu Mun, John H. L. Hansen +1
In language recognition, the task of rejecting/differentiating closely spaced versus acoustically far spaced languages remains a major challenge. For confusable closely spaced lang…