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有声思维和刺激性回忆作为数据采集方式和数据分析对象已被融入应用语言学混合研究当中，其在混合设计中作为质化分析对象的情况仍然占有较大的比重。虽然我们可以像分析语篇那样对口头报告的内容进行质化分析，但其可被量化的特征也尤为突出。在混合设计中，同步报告与量化分析、追溯报告与质化分析之间具有较强的关联性，而其在实验方法中，作为质化分析数据的情况更多。在口头报告仅用于质化分析的文献中，口头报告体现出了更强的...
赣南师范大学外国语学院应用语言学课件Lecture 3 Vocabulary Learning and Strategies。
If Your Child Is Bilingual,Learning Additional Languages Later Might Be Easier（图）
Your Child Bilingual Learning Additional Languages Later Might Be Easier
2017/10/2
It is often claimed that bilinguals are better than monolinguals at learning languages. Now, the first study to examine bilingual and monolingual brains as they learn an additional language offers new...
Child’s Home Learning Environment Predicts 5th Grade Academic Skills（图）
Child’s Home Learning Environment Predicts 5th Grade Academic Skills
2017/8/15
The study, published online in the journal Applied Developmental Science, followed a group of children from birth through 5th grade to track the influence of early home learning environments on later ...
Toddlers begin learning rules of reading,writing at very early age,study finds（图）
Toddlers learning rules of reading writing very early age
2017/7/25
Even the proudest of parents may struggle to find some semblance of meaning behind the seemingly random mish-mash of letters that often emerge from a toddler’s first scribbled and scrawled attempts at...
Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised Learning
Semi-Supervised Unsupervised Learning
2017/4/6
Highly frequent in language and communication, metaphor represents a significant challenge
for Natural Language Processing (NLP) applications. Computational work on metaphor has
traditionally evolve...
Online Learning for Statistical Machine Translation
Online Learning Statistical Machine Translation
2016/4/7
We present online learning techniques for statistical machine translation (SMT). The availability of large training data sets that grow constantly over time is becoming more and more frequent in the f...
Thinking and Language Learning.
基于Active Learning的中文分词领域自适应
中文分词 领域自适应 主动学习
2015/11/14
在新闻领域标注语料上训练的中文分词系统在跨领域时性能会有明显下降。针对目标领域的大规模标注语料难以获取的问题,该文提出Active learning算法与n-gram统计特征相结合的领域自适应方法。该方法通过对目标领域文本与已有标注语料的差异进行统计分析,选择含有最多未标记过的语言现象的小规模语料优先进行人工标注,然后再结合大规模文本中的n-gram统计特征训练目标领域的分词系统。该文采用了CRF...
Cross-lingual Sentiment Lexicon Learning With Bilingual Word Graph Label Propagation
Sentiment Lexicon Learning Bilingual Word Graph Label
2015/9/15
In this article we address the task of cross-lingual sentiment lexicon learning, which aims to automatically generate sentiment lexicons for the target languages with available English sentiment lexic...
Entailment rules between predicates are fundamental to many semantic-inference applications. Consequently, learning such rules has been an active field of research in recent years. Methods for learnin...
Empirical Risk Minimization for Probabilistic Grammars:Sample Complexity and Hardness of Learning
Risk Minimization Probabilistic Grammars Sample Complexity and Hardness
2015/9/10
Probabilistic grammars are generative statistical models that are useful for compositional and sequential structures. They are used ubiquitously in computational linguistics. We present a framework, r...
This article presents our work on constructing a corpus of news articles in which events are annotated for estimated bounds on their duration, and automatically learning from this corpus. We describe ...
Learning and Evaluation of Dialogue Strategies for New Applications: Empirical Methods for Optimization from Small Data Sets
New Applications Small Data Sets
2015/9/9
We present a new data-driven methodology for simulation-based dialogue strategy learning,
which allows us to address several problems in the field of automatic optimization of dialogue
strateg...
Learning Tractable Word Alignment Models with Complex Constraints
Learning Tractable Word Alignment Models Complex Constraints
2015/9/8
Word-level alignment of bilingual text is a critical resource for a growing variety of tasks. Probabilistic models for word alignment present a fundamental trade-off between richness of captured const...