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Cross-lingual word embeddings

Author: Anders Søgaard; Ivan Vulić; Sebastian Ruder; Manaal Faruq
Publisher: [San Rafael, California] : Morgan & Claypool, [2019]
Series: Synthesis lectures on human language technologies, lecture #42.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
The majority of natural language processing (NLP) is English language processing, and while there is good language technology support for (standard varieties of) English, support for Albanian, Burmese, or Cebuano--and most other languages--remains limited. Being able to bridge this digital divide is important for scientific and democratic reasons but also represents an enormous growth potential. A key challenge for  Read more...
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Details

Genre/Form: Electronic books
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Anders Søgaard; Ivan Vulić; Sebastian Ruder; Manaal Faruq
ISBN: 1681730642 9781681730646
OCLC Number: 1107281364
Description: 1 online resource (xi, 120 pages) : illustrations (some color)
Contents: 1. Introduction --
2. Monolingual word embedding models --
3. Cross-lingual word embedding models : typology --
4. A brief history of cross-lingual word representations --
4.1. Cross-lingual word representations using bilingual lexicons --
4.2. Cross-lingual word embeddings and word alignments --
4.3. Representations based on latent and explicit cross-lingual concepts --
4.4. Summary 5. Word-level alignment models --
5.1. Word-level alignment methods with parallel data --
5.2. Word-level alignment methods with comparable data 6. Sentence-level alignment methods --
6.1. Sentence-level methods with parallel data --
6.2. Sentence alignment with comparable data 7. Document-level alignment models --
7.1. Document alignment with comparable data 8. From bilingual to multilingual training --
8.1. Multilingual word embeddings from word-level information --
8.2. Multilingual word embeddings from sentence-level and document-level information 9. Unsupervised learning of cross-lingual word embeddings --
9.1. Seed dictionary induction --
9.2. Refinement and heuristics --
9.3. Limitations of unsupervised approaches 10. Applications and evaluation --
10.1. Intrinsic evaluation --
10.2. Extrinsic evaluation through cross-lingual transfer --
10.3. Multi-modal and cognitive approaches to evaluation 11. Useful data and software --
11.1. Monolingual resources --
11.2. Cross-lingual data --
11.3. Cross-lingual word embedding models --
11.4. Evaluation and application --
12. General challenges and future directions.
Series Title: Synthesis lectures on human language technologies, lecture #42.
Responsibility: Anders Søgaard, Ivan Vulić, Sebastian Ruder, Manaal Faruq.
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Abstract:

Focuses on so-called cross-lingual word embeddings. This survey is intended to be systematic, using consistent notation and putting the available methods on comparable form, making it easy to compare  Read more...

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