16 citations · 30 across the 11 of their papers we have counts for
5 papers · 1 filter
Unconstrained Dysfluency Modeling for Dysfluent Speech Transcription and Detection
Jiachen Lian, Carly Feng, Naasir Farooqi +7
Dysfluent speech modeling requires time-accurate and silence-aware transcription at both the word-level and phonetic-level. However, current research in dysfluency modeling primari…
SD-HuBERT: Sentence-Level Self-Distillation Induces Syllabic Organization in HuBERT
Cheol Jun Cho, Abdelrahman Mohamed, Shang-Wen Li +2
Data-driven unit discovery in self-supervised learning (SSL) of speech has embarked on a new era of spoken language processing. Yet, the discovered units often remain in phonetic s…
Self-Supervised Models of Speech Infer Universal Articulatory Kinematics
Cheol Jun Cho, Abdelrahman Mohamed, Alan W Black +1
Self-Supervised Learning (SSL) based models of speech have shown remarkable performance on a range of downstream tasks. These state-of-the-art models have remained blackboxes, but…
Neural Latent Aligner: Cross-trial Alignment for Learning Representations of Complex, Naturalistic Neural Data
Cheol Jun Cho, Edward F. Chang, Gopala K. Anumanchipalli
Understanding the neural implementation of complex human behaviors is one of the major goals in neuroscience. To this end, it is crucial to find a true representation of the neural…
Speaker-Independent Acoustic-to-Articulatory Speech Inversion
Peter Wu, Li-Wei Chen, Cheol Jun Cho +4
To build speech processing methods that can handle speech as naturally as humans, researchers have explored multiple ways of building an invertible mapping from speech to an interp…