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检索条件"机构=Center for Language and Speech Processing & Human Language Technology"
422 条 记 录,以下是101-110 订阅
排序:
Incorporating Ultrasound Tongue Images for Audio-Visual speech Enhancement
arXiv
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arXiv 2023年
作者: Zheng, Rui-Chen Ai, Yang Ling, Zhen-Hua National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei230027 China
Audio-visual speech enhancement (AV-SE) aims to enhance degraded speech along with extra visual information such as lip videos, and has been shown to be more effective than audio-only speech enhancement. This paper pr... 详细信息
来源: 评论
Long-frame-shift Neural speech Phase Prediction with Spectral Continuity Enhancement and Interpolation Error Compensation
arXiv
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arXiv 2023年
作者: Ai, Yang Lu, Ye-Xin Ling, Zhen-Hua National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei230027 China
speech phase prediction, which is a significant research focus in the field of signal processing, aims to recover speech phase spectra from amplitude-related features. However, existing speech phase prediction methods... 详细信息
来源: 评论
Explicit Estimation of Magnitude and Phase Spectra in Parallel for High-Quality speech Enhancement
arXiv
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arXiv 2023年
作者: Lu, Ye-Xin Ai, Yang Ling, Zhen-Hua The National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei230027 China
Phase information has a significant impact on speech perceptual quality and intelligibility. However, existing speech enhancement methods encounter limitations in explicit phase estimation due to the non-structural na... 详细信息
来源: 评论
language-Independent Prosody-Enhanced speech Representations For Multilingual speech Synthesis
Language-Independent Prosody-Enhanced Speech Representations...
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IEEE Spoken language technology Workshop
作者: Chang Liu Zhen-Hua Ling Ya-Jun Hu National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China China iFLYTEK Co. Ltd. China
This paper proposes language-independent prosody-enhanced speech representations to improve the naturalness of speech synthesis for the target languages that lack prosodic labels. To build text-to-speech (TTS) systems... 详细信息
来源: 评论
Within- and Between-Class Sample Interpolation Based Supervised Metric Learning for Speaker Verification  1
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18th National Conference on Man-Machine speech Communication, NCMMSC 2023
作者: Zhang, Jian-Tao Song, Hao-Yu Guo, Wu Song, Yan Dai, Li-Rong National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei China The Australian National University Canberra Australia
Metric learning aims to pull together the samples belonging to the same class and push apart those from different classes in embedding space. Existing methods may suffer from inadequate and low-quality sample pairs, r... 详细信息
来源: 评论
Leveraging Prompt Learning and Pause Encoding for Alzheimer's Disease Detection
Leveraging Prompt Learning and Pause Encoding for Alzheimer'...
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International Symposium on Chinese Spoken language processing
作者: Yin-Long Liu Rui Feng Jia-Hong Yuan Zhen-Hua Ling National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei Interdisciplinary Research Center for Linguistic Sciences University of Science and Technology of China Hefei
Compared to other clinical screening techniques, speech-and-language-based automated Alzheimer's disease (AD) detection methods are characterized by their non-invasiveness, cost-effectiveness, and convenience. Pre... 详细信息
来源: 评论
An investigation of phrase break prediction in an End-to-End TTS system
arXiv
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arXiv 2023年
作者: Vadapalli, Anandaswarup Speech Processing Lab Language Technologies Research Center International Institute of Information Technology Telangana Hyderabad500032 India
Purpose: This work explores the use of external phrase break prediction models to enhance listener comprehension in End-to-End Text-to-speech (TTS) systems. Methods: The effectiveness of these models is evaluated base... 详细信息
来源: 评论
Joint Energy-Based Model for Robust speech Classification System Against Dirty-Label Backdoor Poisoning Attacks
Joint Energy-Based Model for Robust Speech Classification Sy...
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IEEE Workshop on Automatic speech Recognition and Understanding
作者: Martin Sustek Sonal Joshi Henry Li Thomas Thebaud Jesús Villalba Sanjeev Khudanpur Najim Dehak Center for Language and Speech Processing Johns Hopkins University Baltimore MD USA Faculty of Information Technology Brno University of Technology Czechia
Our novel technique utilizes a Joint Energy-based Model (JEM) that integrates both discriminative and generative approaches to increase resistance against dirty-label backdoor attacks. Our approach is especially effec...
来源: 评论
DuTa-VC: A Duration-aware Typical-to-atypical Voice Conversion Approach with Diffusion Probabilistic Model
arXiv
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arXiv 2023年
作者: Wang, Helin Thebaud, Thomas Villalba, Jesús Sydnor, Myra Lammers, Becky Dehak, Najim Moro-Velazquez, Laureano Center for Language and Speech Processing Johns Hopkins University United States Human Language Technology Center of Excellence Johns Hopkins University United States Department of Physical Medicine and Rehabilitation Johns Hopkins University School of Medicine United States
We present a novel typical-to-atypical voice conversion approach (DuTa-VC), which (i) can be trained with nonparallel data (ii) first introduces diffusion probabilistic model (iii) preserves the target speaker identit... 详细信息
来源: 评论
PERTURBATION-RESTRAINED SEQUENTIAL MODEL EDITING
arXiv
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arXiv 2024年
作者: Ma, Jun-Yu Wang, Hong Xu, Hao-Xiang Ling, Zhen-Hua Gu, Jia-Chen University of Science and Technology of China China National Engineering Research Center of Speech and Language Information Processing China University of California Los Angeles United States
Model editing is an emerging field that focuses on updating the knowledge embedded within large language models (LLMs) without extensive retraining. However, current model editing methods significantly compromise the ... 详细信息
来源: 评论