Search Results for author: Hao Che

Found 7 papers, 1 papers with code

Towards a General Market for Cloud-Edge-IoT Continuum

no code implementations23 Sep 2024 Hao Che, Hong Jiang, Zhijun Wang

While preventing seller lock-in and improving efficiency and availability, a VSM suffers from a key weakness from a buyer's perspective, i. e., the broker and the corresponding marketplace lock-in, which may lead to suboptimal shopping experience for buyers, due to marketplace monopoly by the broker and limited choice of products in the marketplace.

VQ-CTAP: Cross-Modal Fine-Grained Sequence Representation Learning for Speech Processing

no code implementations11 Aug 2024 Chunyu Qiang, Wang Geng, Yi Zhao, Ruibo Fu, Tao Wang, Cheng Gong, Tianrui Wang, Qiuyu Liu, Jiangyan Yi, Zhengqi Wen, Chen Zhang, Hao Che, Longbiao Wang, Jianwu Dang, JianHua Tao

For tasks such as text-to-speech (TTS), voice conversion (VC), and automatic speech recognition (ASR), a cross-modal fine-grained (frame-level) sequence representation is desired, emphasizing the semantic content of the text modality while de-emphasizing the paralinguistic information of the speech modality.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +5

Style-Label-Free: Cross-Speaker Style Transfer by Quantized VAE and Speaker-wise Normalization in Speech Synthesis

no code implementations13 Dec 2022 Chunyu Qiang, Peng Yang, Hao Che, Xiaorui Wang, Zhongyuan Wang

In order to improve the style extraction ability of the reference encoder, a style invariant and contrastive data augmentation method is proposed.

Data Augmentation Speech Synthesis +1

Back-Translation-Style Data Augmentation for Mandarin Chinese Polyphone Disambiguation

no code implementations17 Nov 2022 Chunyu Qiang, Peng Yang, Hao Che, Jinba Xiao, Xiaorui Wang, Zhongyuan Wang

In this paper we propose a simple back-translation-style data augmentation method for mandarin Chinese polyphone disambiguation, utilizing a large amount of unlabeled text data.

Data Augmentation Machine Translation +5

Multi-layered Semantic Representation Network for Multi-label Image Classification

1 code implementation22 Jun 2021 Xiwen Qu, Hao Che, Jun Huang, Linchuan Xu, Xiao Zheng

To this end, this paper designs a Multi-layered Semantic Representation Network (MSRN) which discovers both local and global semantics of labels through modeling label correlations and utilizes the label semantics to guide the semantic representations learning at multiple layers through an attention mechanism.

Classification Multi-Label Classification +1

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