2 citations · 3 across the 5 of their papers we have counts for
8 papers
Toward a Universal Local Speech Feature Extractor Through Distillation
Jessica Yang, Marcelo Beramendi Caballero, Ju-Chieh Chou +1
Self-supervised speech models commonly consist of a set of convolutional neural network (CNN) layers used as a local feature extractor, followed by transformer layers. The CNN laye…
Distilling Text LMs into Speech-to-Speech LMs by Matching Internal Text Predictions
Ju-Chieh Chou, Jiawei Zhou, Karen Livescu
Text language models (LMs) acquire broad linguistic and factual capabilities through large-scale pretraining, while comparable capabilities remain difficult to learn from speech al…
Quantifying the Generation Modality Gap in Speech-Text Language Models
Ju-Chieh Chou, Jiawei Zhou, Karen Livescu
Pure speech language models often lag behind text and speech-text language models in generating coherent content, but this gap is difficult to quantify because speech and text syst…
Flow-SLM: Joint Learning of Linguistic and Acoustic Information for Spoken Language Modeling
Ju-Chieh Chou, Jiawei Zhou, Karen Livescu
Textless spoken language models (SLMs) are generative models of speech that do not rely on text supervision. Most textless SLMs learn to predict the next semantic token, a discrete…
Speech Recognition for Analysis of Police Radio Communication
Tejes Srivastava, Ju-Chieh Chou, Priyank Shroff +2
Police departments around the world use two-way radio for coordination. These broadcast police communications (BPC) are a unique source of information about everyday police activit…
Toward Joint Language Modeling for Speech Units and Text
Ju-Chieh Chou, Chung-Ming Chien, Wei-Ning Hsu +5
Speech and text are two major forms of human language. The research community has been focusing on mapping speech to text or vice versa for many years. However, in the field of lan…
Few-Shot Spoken Language Understanding via Joint Speech-Text Models
Chung-Ming Chien, Mingjiamei Zhang, Ju-Chieh Chou +1
Recent work on speech representation models jointly pre-trained with text has demonstrated the potential of improving speech representations by encoding speech and text in a shared…
AV2Wav: Diffusion-Based Re-synthesis from Continuous Self-supervised Features for Audio-Visual Speech Enhancement
Ju-Chieh Chou, Chung-Ming Chien, Karen Livescu
Speech enhancement systems are typically trained using pairs of clean and noisy speech. In audio-visual speech enhancement (AVSE), there is not as much ground-truth clean data avai…