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Found 10 papers, 3 papers with code
MMAR: Towards Lossless Multi-Modal Auto-Regressive Probabilistic Modeling
However, we have identified that recent methods inevitably suffer from loss of image information during understanding task, due to either image discretization or diffusion denoising steps.
Ranked #212 on
Visual Question Answering
on MM-Vet
ART$\boldsymbol{\cdot}$V: Auto-Regressive Text-to-Video Generation with Diffusion Models
Second, it preserves the high-fidelity generation ability of the pre-trained image diffusion models by making only minimal network modifications.
MicroCinema: A Divide-and-Conquer Approach for Text-to-Video Generation
We present MicroCinema, a straightforward yet effective framework for high-quality and coherent text-to-video generation.
Filler Word Detection with Hard Category Mining and Inter-Category Focal Loss
Filler words like ``um" or ``uh" are common in spontaneous speech.
TridentSE: Guiding Speech Enhancement with 32 Global Tokens
In this paper, we present TridentSE, a novel architecture for speech enhancement, which is capable of efficiently capturing both global information and local details.
RetrieverTTS: Modeling Decomposed Factors for Text-Based Speech Insertion
In the proposed paradigm, global and local factors in speech are explicitly decomposed and separately manipulated to achieve high speaker similarity and continuous prosody.
Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph
Last, an innovative link attention module serves as the decoder to reconstruct data from the decomposed content and style, with the help of the linking keys.
Zero-Shot Text-to-Speech for Text-Based Insertion in Audio Narration
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
This paper presents a self-supervised learning framework, named MGF, for general-purpose speech representation learning.
PHASEN: A Phase-and-Harmonics-Aware Speech Enhancement Network
We discover that the two streams should communicate with each other, and this is crucial to phase prediction.
Sound Audio and Speech Processing
