27 citations · 57 across the 9 of their papers we have counts for
9 papers
L-Proto: Language-Aware Episodic Prototypical Training for Multilingual Speaker Verification
Hyung-Seok Oh, Deok-Hyeon Cho, Seung-Bin Kim +1
Multilingual speaker verification remains challenging because language-dependent acoustic variability causes speaker identity to become entangled with linguistic characteristics, d…
Affectron: Emotional Speech Synthesis with Affective and Contextually Aligned Nonverbal Vocalizations
Deok-Hyeon Cho, Hyung-Seok Oh, Seung-Bin Kim +1
Nonverbal vocalizations (NVs), such as laughter and sighs, are central to the expression of affective cues in emotional speech synthesis. However, learning diverse and contextually…
Toward Complex-Valued Neural Networks for Waveform Generation
Hyung-Seok Oh, Deok-Hyeon Cho, Seung-Bin Kim +1
Neural vocoders have recently advanced waveform generation, yielding natural and expressive audio. Among these approaches, iSTFT-based vocoders have recently gained attention. They…
Spotlight-TTS: Spotlighting the Style via Voiced-Aware Style Extraction and Style Direction Adjustment for Expressive Text-to-Speech
Nam-Gyu Kim, Deok-Hyeon Cho, Seung-Bin Kim +1
Recent advances in expressive text-to-speech (TTS) have introduced diverse methods based on style embedding extracted from reference speech. However, synthesizing high-quality expr…
EmoSphere-SER: Enhancing Speech Emotion Recognition Through Spherical Representation with Auxiliary Classification
Deok-Hyeon Cho, Hyung-Seok Oh, Seung-Bin Kim +1
Speech emotion recognition predicts a speaker's emotional state from speech signals using discrete labels or continuous dimensions such as arousal, valence, and dominance (VAD). We…
DiEmo-TTS: Disentangled Emotion Representations via Self-Supervised Distillation for Cross-Speaker Emotion Transfer in Text-to-Speech
Deok-Hyeon Cho, Hyung-Seok Oh, Seung-Bin Kim +1
Cross-speaker emotion transfer in speech synthesis relies on extracting speaker-independent emotion embeddings for accurate emotion modeling without retaining speaker traits. Howev…
EmoSphere++: Emotion-Controllable Zero-Shot Text-to-Speech via Emotion-Adaptive Spherical Vector
Deok-Hyeon Cho, Hyung-Seok Oh, Seung-Bin Kim +1
Emotional text-to-speech (TTS) technology has achieved significant progress in recent years; however, challenges remain owing to the inherent complexity of emotions and limitations…
EmoSphere-TTS: Emotional Style and Intensity Modeling via Spherical Emotion Vector for Controllable Emotional Text-to-Speech
Deok-Hyeon Cho, Hyung-Seok Oh, Seung-Bin Kim +2
Despite rapid advances in the field of emotional text-to-speech (TTS), recent studies primarily focus on mimicking the average style of a particular emotion. As a result, the abili…
DurFlex-EVC: Duration-Flexible Emotional Voice Conversion Leveraging Discrete Representations without Text Alignment
Hyung-Seok Oh, Sang-Hoon Lee, Deok-Hyeon Cho +1
Emotional voice conversion (EVC) involves modifying various acoustic characteristics, such as pitch and spectral envelope, to match a desired emotional state while preserving the s…