26 citations · 39 across the 10 of their papers we have counts for
10 papers
MicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation
Yanhui Wang, Jianmin Bao, Wenming Weng +12
We present MicroCinema, a straightforward yet effective framework for high-quality and coherent text-to-video generation. Unlike existing approaches that align text prompts with vi…
ARTV: Auto-Regressive Text-to-Video Generation with Diffusion Models
Wenming Weng, Ruoyu Feng, Yanhui Wang +10
We present ARTV, an efficient framework for auto-regressive video generation with diffusion models. Unlike existing methods that generate entire videos in one-s…
Filler Word Detection with Hard Category Mining and Inter-Category Focal Loss
Zhiyuan Zhao, Lijun Wu, Chuanxin Tang +3
Filler words like ``um" or ``uh" are common in spontaneous speech. It is desirable to automatically detect and remove them in recordings, as they affect the fluency, confidence, an…
Learning Trajectories are Generalization Indicators
Jingwen Fu, Zhizheng Zhang, Dacheng Yin +2
This paper explores the connection between learning trajectories of Deep Neural Networks (DNNs) and their generalization capabilities when optimized using (stochastic) gradient des…
TridentSE: Guiding Speech Enhancement with 32 Global Tokens
Dacheng Yin, Zhiyuan Zhao, Chuanxin Tang +2
In this paper, we present TridentSE, a novel architecture for speech enhancement, which is capable of efficiently capturing both global information and local details. TridentSE mai…
RetrieverTTS: Modeling Decomposed Factors for Text-Based Speech Insertion
Dacheng Yin, Chuanxin Tang, Yanqing Liu +6
This paper proposes a new "decompose-and-edit" paradigm for the text-based speech insertion task that facilitates arbitrary-length speech insertion and even full sentence generatio…
Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph
Dacheng Yin, Xuanchi Ren, Chong Luo +3
This paper addresses the unsupervised learning of content-style decomposed representation. We first give a definition of style and then model the content-style representation as a…
Zero-Shot Text-to-Speech for Text-Based Insertion in Audio Narration
Chuanxin Tang, Chong Luo, Zhiyuan Zhao +3
Given a piece of speech and its transcript text, text-based speech editing aims to generate speech that can be seamlessly inserted into the given speech by editing the transcript.…
General-Purpose Speech Representation Learning through a Self-Supervised Multi-Granularity Framework
Yucheng Zhao, Dacheng Yin, Chong Luo +4
This paper presents a self-supervised learning framework, named MGF, for general-purpose speech representation learning. In the design of MGF, speech hierarchy is taken into consid…
PHASEN: A Phase-and-Harmonics-Aware Speech Enhancement Network
Dacheng Yin, Chong Luo, Zhiwei Xiong +1
Time-frequency (T-F) domain masking is a mainstream approach for single-channel speech enhancement. Recently, focuses have been put to phase prediction in addition to amplitude pre…