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1
Automated Assessment of Glottal Dysfunction Through Unified Acoustic Voice Analysis
In: ISSN: 0892-1997 ; Journal of Voice ; https://hal.archives-ouvertes.fr/hal-02987882 ; Journal of Voice, Elsevier, In press, ⟨10.1016/j.jvoice.2020.08.032⟩ (2021)
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2
XLST: Cross-lingual Self-training to Learn Multilingual Representation for Low Resource Speech Recognition ...
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3
Improving Arabic Diacritization with Regularized Decoding and Adversarial Training ...
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4
Cross-modal Memory Networks for Radiology Report Generation ...
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5
Improving Federated Learning for Aspect-based Sentiment Analysis via Topic Memories ...
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6
Relation Extraction with Type-aware Map Memories of Word Dependencies ...
Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.221 Abstract: Relation extraction is an important task in information extraction and retrieval that aims to extract relations among the given entities from running texts. To achieve a good performance for this task, previous studies have shown that a good modeling of the contextual information is required, where the dependency tree of the input sentence can be a beneficial source among different types of contextual information. However, most of these studies focus on the dependency connections between words with limited attention paid to exploiting dependency types. In addition, they often treat different dependency connections equally in modeling so that suffer from the noise (inaccurate dependency parses) in the auto-generated dependency tree. In this paper, we propose a neural approach for relation extraction, with type-aware map memories (TaMM) for encoding dependency types obtained from an off-the-shelf dependency parser for the input sentence. ...
URL: https://underline.io/lecture/26312-relation-extraction-with-type-aware-map-memories-of-word-dependencies
https://dx.doi.org/10.48448/87qh-sx95
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7
Federated Chinese Word Segmentation with Global Character Associations ...
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8
Relation Extraction with Word Graphs from N-grams ...
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9
Dependency-driven Relation Extraction with Attentive Graph Convolutional Networks ...
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10
Early Top-Down Modulation in Visual Word Form Processing: Evidence From an Intracranial SEEG Study
In: J Neurosci (2021)
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11
Joint Chinese Word Segmentation and Part-of-speech Tagging via Multi-channel Attention of Character N-grams ...
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12
Supertagging Combinatory Categorial Grammar with Attentive Graph Convolutional Networks ...
Tian, Yuanhe; Song, Yan; Xia, Fei. - : arXiv, 2020
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13
A Joint Model of Conversational Discourse and Latent Topics on Microblogs ...
Li, Jing; Song, Yan; Wei, Zhongyu. - : arXiv, 2018
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14
LID-senones and their statistics for language identification
Jin, Ma; Song, Yan; McLoughlin, Ian Vince. - : Institute of Electrical and Electronics Engineers, 2017
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15
Improvements on Deep Bottleneck Network based I-Vector Representation for Spoken Language Identification
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16
Improved language identification using deep bottleneck network
Song, Yan; Cui, Ruilian; Hong, Xinhai. - : IEEE, 2016
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17
Deep Bottleneck Network based i-vector representation for Language Identification
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18
Deep Bottleneck Feature for Image Classification
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19
Reconstruction of Phonated Speech from Whispers Using Formant-Derived Plausible Pitch Modulation
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20
A Perceptual Learning Deficit in Chinese Developmental Dyslexia as Revealed by Visual Texture Discrimination Training
In: Dyslexia. - Bracknell : British Dyslexia Association 20 (2014) 3, 280-296
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