1 citations · 1 across the 14 of their papers we have counts for
18 papers
Probing Neural Audio Codecs with Speaker Traits and Speech Characteristics
Jihwan Lee, Tiantian Feng, Minu Kim +6
Neural audio codecs are increasingly used for low-bitrate speech coding and serve as tokenizers for speech language models, yet it remains unclear how their codebook hierarchies en…
Affect Decoding in Phonated and Silent Speech Production from Surface EMG
Simon Pistrosch, Kleanthis Avramidis, Zhao Ren +7
The expression of affect is integral to spoken communication, yet, its link to underlying articulatory execution remains unclear. Measures of articulatory muscle activity such as E…
Learning-free L2-Accented Speech Generation using Phonological Rules
Thanathai Lertpetchpun, Yoonjeong Lee, Jihwan Lee +3
Accent plays a crucial role in speaker identity and inclusivity in speech technologies. Existing accented text-to-speech (TTS) systems either require large-scale accented datasets…
Accent Vector: Controllable Accent Manipulation for Multilingual TTS Without Accented Data
Thanathai Lertpetchpun, Thanapat Trachu, Jihwan Lee +3
Accent is an integral part of society, reflecting multiculturalism and shaping how individuals express identity. The majority of English speakers are non-native (L2) speakers, yet…
Reconstruct! Don't Encode: Self-Supervised Representation Reconstruction Loss for High-Intelligibility and Low-Latency Streaming Neural Audio Codec
Junhyeok Lee, Xiluo He, Jihwan Lee +6
Neural audio codecs optimized for mel-spectrogram reconstruction often fail to preserve intelligibility. While semantic encoder distillation improves encoded representations, it do…
An Approach to Simultaneous Acquisition of Real-Time MRI Video, EEG, and Surface EMG for Articulatory, Brain, and Muscle Activity During Speech Production
Jihwan Lee, Parsa Razmara, Kevin Huang +16
Speech production is a complex process spanning neural planning, motor control, muscle activation, and articulatory kinematics. While the acoustic speech signal is the most accessi…
Quantifying Speaker Embedding Phonological Rule Interactions in Accented Speech Synthesis
Thanathai Lertpetchpun, Yoonjeong Lee, Thanapat Trachu +4
Many spoken languages, including English, exhibit wide variation in dialects and accents, making accent control an important capability for flexible text-to-speech (TTS) models. Cu…
Neural Codecs as Biosignal Tokenizers
Kleanthis Avramidis, Tiantian Feng, Woojae Jeong +4
Neurophysiological recordings such as electroencephalography (EEG) offer accessible and minimally invasive means of estimating physiological activity for applications in healthcare…
A long-form single-speaker real-time MRI speech dataset and benchmark
Sean Foley, Jihwan Lee, Kevin Huang +4
We release the USC Long Single-Speaker (LSS) dataset containing real-time MRI video of the vocal tract dynamics and simultaneous audio obtained during speech production. This uniqu…
ARTI-6: Towards Six-dimensional Articulatory Speech Encoding
Jihwan Lee, Sean Foley, Thanathai Lertpetchpun +6
We propose ARTI-6, a compact six-dimensional articulatory speech encoding framework derived from real-time MRI data that captures crucial vocal tract regions including the velum, t…
Interpretable Modeling of Articulatory Temporal Dynamics from real-time MRI for Phoneme Recognition
Jay Park, Hong Nguyen, Sean Foley +4
Real-time Magnetic Resonance Imaging (rtMRI) visualizes vocal tract action, offering a comprehensive window into speech articulation. However, its signals are high dimensional and…
Voxlect: A Speech Foundation Model Benchmark for Modeling Dialects and Regional Languages Around the Globe
Tiantian Feng, Kevin Huang, Anfeng Xu +6
We present Voxlect, a novel benchmark for modeling dialects and regional languages worldwide using speech foundation models. Specifically, we report comprehensive benchmark evaluat…
On the Relationship between Accent Strength and Articulatory Features
Kevin Huang, Sean Foley, Jihwan Lee +3
This paper explores the relationship between accent strength and articulatory features inferred from acoustic speech. To quantify accent strength, we compare phonetic transcription…
Towards disentangling the contributions of articulation and acoustics in multimodal phoneme recognition
Sean Foley, Hong Nguyen, Jihwan Lee +4
Although many previous studies have carried out multimodal learning with real-time MRI data that captures the audio-visual kinematics of the vocal tract during speech, these studie…
Articulatory Feature Prediction from Surface EMG during Speech Production
Jihwan Lee, Kevin Huang, Kleanthis Avramidis +6
We present a model for predicting articulatory features from surface electromyography (EMG) signals during speech production. The proposed model integrates convolutional layers and…
Vox-Profile: A Speech Foundation Model Benchmark for Characterizing Diverse Speaker Traits and Speech Properties
Tiantian Feng, Jihwan Lee, Anfeng Xu +9
We introduce Vox-Profile, a comprehensive benchmark to characterize rich speaker traits and speech properties using speech foundation models. Unlike prior work that targets a singl…
Enhancing Listened Speech Decoding from EEG via Parallel Phoneme Sequence Prediction
Jihwan Lee, Tiantian Feng, Aditya Kommineni +2
Brain-computer interfaces (BCI) offer numerous human-centered application possibilities, particularly affecting people with neurological disorders. Text or speech decoding from bra…
Toward Fully-End-to-End Listened Speech Decoding from EEG Signals
Jihwan Lee, Aditya Kommineni, Tiantian Feng +4
Speech decoding from EEG signals is a challenging task, where brain activity is modeled to estimate salient characteristics of acoustic stimuli. We propose FESDE, a novel framework…