Zobrazeno 1 - 10
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pro vyhledávání: '"Zhao, Guoqing"'
Autor:
Chen, Zhigang, Zhou, Benjia, Li, Jun, Wan, Jun, Lei, Zhen, Jiang, Ning, Lu, Quan, Zhao, Guoqing
Previous Sign Language Translation (SLT) methods achieve superior performance by relying on gloss annotations. However, labeling high-quality glosses is a labor-intensive task, which limits the further development of SLT. Although some approaches wor
Externí odkaz:
http://arxiv.org/abs/2403.12556
Language models (LMs) have shown superior performances in various speech generation tasks recently, demonstrating their powerful ability for semantic context modeling. Given the intrinsic similarity between speech generation and speech enhancement, h
Externí odkaz:
http://arxiv.org/abs/2312.09747
This paper aims to build a multi-speaker expressive TTS system, synthesizing a target speaker's speech with multiple styles and emotions. To this end, we propose a novel contrastive learning-based TTS approach to transfer style and emotion across spe
Externí odkaz:
http://arxiv.org/abs/2310.17101
Multi-objective Progressive Clustering for Semi-supervised Domain Adaptation in Speaker Verification
Utilizing the pseudo-labeling algorithm with large-scale unlabeled data becomes crucial for semi-supervised domain adaptation in speaker verification tasks. In this paper, we propose a novel pseudo-labeling method named Multi-objective Progressive Cl
Externí odkaz:
http://arxiv.org/abs/2310.04760
It is widely acknowledged that discriminative representation for speaker verification can be extracted from verbal speech. However, how much speaker information that non-verbal vocalization carries is still a puzzle. This paper explores speaker verif
Externí odkaz:
http://arxiv.org/abs/2309.14109
This paper is the system description of the DKU-MSXF System for the track1, track2 and track3 of the VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23). For Track 1, we utilize a network structure based on ResNet for training. By constructing a
Externí odkaz:
http://arxiv.org/abs/2308.08766
This paper describes the DKU-MSXF submission to track 4 of the VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23). Our system pipeline contains voice activity detection, clustering-based diarization, overlapped speech detection, and target-speak
Externí odkaz:
http://arxiv.org/abs/2308.07595
In this paper, we introduce a large-scale and high-quality audio-visual speaker verification dataset, named VoxBlink. We propose an innovative and robust automatic audio-visual data mining pipeline to curate this dataset, which contains 1.45M utteran
Externí odkaz:
http://arxiv.org/abs/2308.07056
Autor:
Song, Kun, lei, Yi, Chen, Peikun, Cao, Yiqing, Wei, Kun, Zhang, Yongmao, Xie, Lei, Jiang, Ning, Zhao, Guoqing
This paper describes the NPU-MSXF system for the IWSLT 2023 speech-to-speech translation (S2ST) task which aims to translate from English speech of multi-source to Chinese speech. The system is built in a cascaded manner consisting of automatic speec
Externí odkaz:
http://arxiv.org/abs/2307.04630
ICD coding is designed to assign the disease codes to electronic health records (EHRs) upon discharge, which is crucial for billing and clinical statistics. In an attempt to improve the effectiveness and efficiency of manual coding, many methods have
Externí odkaz:
http://arxiv.org/abs/2305.18576