139 citations · 230 across the 25 of their papers we have counts for
25 papers
A Novel LLM-based Two-stage Summarization Approach for Long Dialogues
Yuan-Jhe Yin, Bo-Yu Chen, Berlin Chen
Long document summarization poses a significant challenge in natural language processing due to input lengths that exceed the capacity of most state-of-the-art pre-trained language…
Geometric Learning of Hidden Markov Models via a Method of Moments Algorithm
Berlin Chen, Cyrus Mostajeran, Salem Said
We present a novel algorithm for learning the parameters of hidden Markov models (HMMs) in a geometric setting where the observations take values in Riemannian manifolds. In partic…
Exploring Non-Autoregressive End-To-End Neural Modeling For English Mispronunciation Detection And Diagnosis
Hsin-Wei Wang, Bi-Cheng Yan, Hsuan-Sheng Chiu +2
End-to-end (E2E) neural modeling has emerged as one predominant school of thought to develop computer-assisted language training (CAPT) systems, showing competitive performance to…
Improving End-To-End Modeling for Mispronunciation Detection with Effective Augmentation Mechanisms
Tien-Hong Lo, Yao-Ting Sung, Berlin Chen
Recently, end-to-end (E2E) models, which allow to take spectral vector sequences of L2 (second-language) learners' utterances as input and produce the corresponding phone-level seq…
Cross-domain Single-channel Speech Enhancement Model with Bi-projection Fusion Module for Noise-robust ASR
Fu-An Chao, Jeih-weih Hung, Berlin Chen
In recent decades, many studies have suggested that phase information is crucial for speech enhancement (SE), and time-domain single-channel speech enhancement techniques have show…
Maximum F1-score training for end-to-end mispronunciation detection and diagnosis of L2 English speech
Bi-Cheng Yan, Shao-Wei Fan Jiang, Fu-An Chao +1
End-to-end (E2E) neural models are increasingly attracting attention as a promising modeling approach for mispronunciation detection and diagnosis (MDD). Typically, these models ar…