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检索条件"机构=Center for Language and Speech Processing & Human Language Technology"
421 条 记 录,以下是1-10 订阅
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Exploring Geometric Representational Disparities Between Multilingual and Bilingual Translation Models  30
Exploring Geometric Representational Disparities Between Mul...
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Joint 30th International Conference on Computational Linguistics and 14th International Conference on language Resources and Evaluation, LREC-COLING 2024
作者: Verma, Neha Murray, Kenton Duh, Kevin Center for Language and Speech Processing United States Human Language Technology Center of Excellence United States
Multilingual machine translation has proven immensely useful for both parameter efficiency and overall performance across many language pairs via complete multilingual parameter sharing. However, some language pairs i... 详细信息
来源: 评论
Integrating Time-Frequency Domain Shallow and Deep Features for speech-EEG Match-Mismatch of Auditory Attention Decoding
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Journal of Shanghai Jiaotong University (Science) 2025年 1-7页
作者: Zhang, Yubang Zhu, Qiushi Xu, Qingtian Zhang, Jie National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei230026 China
Electroencephalogram (EEG) signals provide an important pathway to reflect brain activations, from which auditory attention clues of the listener can be decoded, termed as auditory attention decoding (AAD). However, e... 详细信息
来源: 评论
JHU IWSLT 2024 Dialectal and Low-resource System Description  21
JHU IWSLT 2024 Dialectal and Low-resource System Description
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21st International Conference on Spoken language Translation, IWSLT 2024
作者: Robinson, Nathaniel R. Sun, Kaiser Xiao, Cihan Bafna, Niyati Tan, Weiting Xu, Haoran Xinyuan, Henry Li Kejriwal, Ankur Khudanpur, Sanjeev Murray, Kenton McNamee, Paul Johns Hopkins University Center for Language and Speech Processing United States Human Language Technology Center of Excellence Baltimore United States
Johns Hopkins University (JHU) submitted systems for all eight language pairs in the 2024 Low-Resource language Track. The main effort of this work revolves around fine-tuning large and publicly available models in th... 详细信息
来源: 评论
Adapting Self-Supervised Models to Multi-Talker speech Recognition Using Speaker Embeddings  48
Adapting Self-Supervised Models to Multi-Talker Speech Recog...
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48th IEEE International Conference on Acoustics, speech and Signal processing, ICASSP 2023
作者: Huang, Zili Raj, Desh Garcia, Paola Khudanpur, Sanjeev Johns Hopkins University Center for Language and Speech Processing Human Language Technology Center of Excellence Baltimore United States
Self-supervised learning (SSL) methods which learn representations of data without explicit supervision have gained popularity in speech-processing tasks, particularly for single-Talker applications. However, these mo... 详细信息
来源: 评论
JHU IWSLT 2023 Dialect speech Translation System Description  20
JHU IWSLT 2023 Dialect Speech Translation System Description
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20th International Conference on Spoken language Translation, IWSLT 2023
作者: Hussein, Amir Xiao, Cihan Verma, Neha Thebaud, Thomas Wiesner, Matthew Khudanpur, Sanjeev Center for Language and Speech Processing United States Human Language Technology Center of Excellence Johns Hopkins University United States
This paper presents JHU’s submissions to the IWSLT 2023 dialectal and low-resource track of Tunisian Arabic to English speech translation. The Tunisian dialect lacks formal orthography and abundant training data, mak... 详细信息
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JHU IWSLT 2023 Multilingual speech Translation System Description  20
JHU IWSLT 2023 Multilingual Speech Translation System Descri...
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20th International Conference on Spoken language Translation, IWSLT 2023
作者: Xinyuan, Henry Li Verma, Neha Odoom, Bismarck Bamfo Pradeep, Ujvala Wiesner, Matthew Khudanpur, Sanjeev Center for Language and Speech Processing United States Human Language Technology Center of Excellence Johns Hopkins University United States
We describe the Johns Hopkins ACL 60-60 speech Translation systems submitted to the IWSLT 2023 Multilingual track, where we were tasked to translate ACL presentations from English into 10 languages. We developed casca... 详细信息
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Importance of Different Temporal Modulations of speech: a Tale of two Perspectives  48
Importance of Different Temporal Modulations of Speech: a Ta...
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48th IEEE International Conference on Acoustics, speech and Signal processing, ICASSP 2023
作者: Sadhu, Samik Hermansky, Hynek Johns Hopkins University Center for Language and Speech Processing United States Johns Hopkins University Human Language Technology Center of Excellence United States
How important are different temporal speech modulations for speech recognition? We answer this question from two complementary perspectives. Firstly, we quantify the amount of phonetic information in the modulation sp... 详细信息
来源: 评论
APCodec+: A Spectrum-Coding-Based High-Fidelity and High-Compression-Rate Neural Audio Codec with Staged Training Paradigm  14
APCodec+: A Spectrum-Coding-Based High-Fidelity and High-Com...
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14th International Symposium on Chinese Spoken language processing, ISCSLP 2024
作者: Du, Hui-Peng Ai, Yang Zheng, Rui-Chen Ling, Zhen-Hua National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei China
This paper proposes a novel neural audio codec, named APCodec+, which is an improved version of APCodec. The APCodec+ takes the audio amplitude and phase spectra as the coding object, and employs an adversarial traini... 详细信息
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APNet2: High-Quality and High-Efficiency Neural Vocoder with Direct Prediction of Amplitude and Phase Spectra  1
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18th National Conference on Man-Machine speech Communication, NCMMSC 2023
作者: Du, Hui-Peng Lu, Ye-Xin Ai, Yang Ling, Zhen-Hua National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei China
In our previous work, we have proposed a neural vocoder called APNet, which directly predicts speech amplitude and phase spectra with a 5 ms frame shift in parallel from the input acoustic features, and then reconstru... 详细信息
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Identifying Context-Dependent Translations for Evaluation Set Production  8
Identifying Context-Dependent Translations for Evaluation Se...
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8th Conference on Machine Translation, WMT 2023
作者: Wicks, Rachel Post, Matt Human Language Technology Center of Excellence Johns Hopkins University United States Center of Language and Speech Processing Johns Hopkins University United States Microsoft United States
A major impediment to the transition to context-aware machine translation is the absence of good evaluation metrics and test sets. Sentences that require context to be translated correctly are rare in test sets, reduc... 详细信息
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