53 citations · 175 across the 22 of their papers we have counts for
11 papers · 1 filter
Audio-Visual Neural Syntax Acquisition
Cheng-I Jeff Lai, Freda Shi, Puyuan Peng +10
We study phrase structure induction from visually-grounded speech. The core idea is to first segment the speech waveform into sequences of word segments, and subsequently induce ph…
Instruction-Following Speech Recognition
Cheng-I Jeff Lai, Zhiyun Lu, Liangliang Cao +1
Conventional end-to-end Automatic Speech Recognition (ASR) models primarily focus on exact transcription tasks, lacking flexibility for nuanced user interactions. With the advent o…
Cascading and Direct Approaches to Unsupervised Constituency Parsing on Spoken Sentences
Yuan Tseng, Cheng-I Lai, Hung-yi Lee
Past work on unsupervised parsing is constrained to written form. In this paper, we present the first study on unsupervised spoken constituency parsing given unlabeled spoken sente…
SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities
Hsiang-Sheng Tsai, Heng-Jui Chang, Wen-Chin Huang +14
Transfer learning has proven to be crucial in advancing the state of speech and natural language processing research in recent years. In speech, a model pre-trained by self-supervi…
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition
Cheng-I Jeff Lai, Yang Zhang, Alexander H. Liu +7
Self-supervised speech representation learning (speech SSL) has demonstrated the benefit of scale in learning rich representations for Automatic Speech Recognition (ASR) with limit…
SUPERB: Speech processing Universal PERformance Benchmark
Shu-wen Yang, Po-Han Chi, Yung-Sung Chuang +17
Self-supervised learning (SSL) has proven vital for advancing research in natural language processing (NLP) and computer vision (CV). The paradigm pretrains a shared model on large…
Conditioned Natural Language Generation using only Unconditioned Language Model: An Exploration
Fan-Keng Sun, Cheng-I Lai
Transformer-based language models have shown to be very powerful for natural language generation (NLG). However, text generation conditioned on some user inputs, such as topics or…
Towards Semi-Supervised Semantics Understanding from Speech
Cheng-I Lai, Jin Cao, Sravan Bodapati +1
Much recent work on Spoken Language Understanding (SLU) falls short in at least one of three ways: models were trained on oracle text input and neglected the Automatics Speech Reco…
Semi-Supervised Spoken Language Understanding via Self-Supervised Speech and Language Model Pretraining
Cheng-I Lai, Yung-Sung Chuang, Hung-Yi Lee +2
Much recent work on Spoken Language Understanding (SLU) is limited in at least one of three ways: models were trained on oracle text input and neglected ASR errors, models were tra…
Contrastive Predictive Coding Based Feature for Automatic Speaker Verification
Cheng-I Lai
This thesis describes our ongoing work on Contrastive Predictive Coding (CPC) features for speaker verification. CPC is a recently proposed representation learning framework based…
ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworks
Cheng-I Lai, Nanxin Chen, Jesús Villalba +1
We present JHU's system submission to the ASVspoof 2019 Challenge: Anti-Spoofing with Squeeze-Excitation and Residual neTworks (ASSERT). Anti-spoofing has gathered more and more at…