| 1 |
Lexical Diversity in Statistical and Neural Machine Translation
|
|
|
|
In: Information; Volume 13; Issue 2; Pages: 93 (2022)
|
|
BASE
|
|
Show details
|
|
|
| 2 |
Multilingual neural architectures for natural language processing ; Architectures neuronales multilingues pour le traitement automatique des langues naturelles
|
|
|
|
In: https://tel.archives-ouvertes.fr/tel-03199494 ; Informatique et langage [cs.CL]. Université du Maine, 2021. Français. ⟨NNT : 2021LEMA1002⟩ (2021)
|
|
BASE
|
|
Show details
|
|
|
| 4 |
Supervised OCR Error Detection and Correction Using Statistical and Neural Machine Translation Methods
|
|
|
|
In: Amrhein, Chantal; Clematide, Simon (2018). Supervised OCR Error Detection and Correction Using Statistical and Neural Machine Translation Methods. Journal for Language Technology and Computational Linguistics (JLCL), 33(1):49-76. (2018)
|
|
BASE
|
|
Show details
|
|
|
| 5 |
A Survey of Current Paradigms in Machine Translation
|
|
|
|
In: DTIC (1998)
|
|
Abstract:
This paper is a survey of machine translation (MT) research from the United States, Europe, and Japan. A short history of machine translation is presented, followed by an overview of current research and representative examples of a wide range of different approaches adopted by machine translation researchers. These examples are described in detail along with a discussion of the practicalities of scaling up such approaches for operational environments. In support of this discussion, issues in, and techniques for, evaluating machine translation systems are discussed. While a number of MT surveys have been published, this one discusses a wide range of current research issues in light of results obtained from a survey and evaluation project conducted by Mitre. During this project, Mitre evaluated 16 MT systems and also studied 7 U.S. MT systems. Because a number of innovative MT approaches have surfaced since the completion of the Mitre study, the authors also include discussions of more recent research paradigms. Section 2 provides a brief description of the history of MT. Section 3 discusses the types of challenges (both linguistic and operational) that one must consider in developing a MT system. Section 4 describes three architectural designs that are used for MT. Following this is a comparison of translation systems along the axis of research paradigms (section 5); these include linguistic, nonlinguistic, and hybrid approaches. Section 6 is a discussion of the challenges of evaluating a MT system, and some approaches to doing so. A 233-item bibliography is included. ; Prepared in cooperation with the Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA and Mitre Corporation, Artificial Intelligence Center, McLean, VA. Report no. CS-TR-3961.
|
|
Keyword:
*ARTIFICIAL INTELLIGENCE; *COMPUTER PROGRAMS; *MACHINE TRANSLATION; *NATURAL LANGUAGE; *SCIENTIFIC RESEARCH; *SOFTWARE ARCHITECTURE; ARCHITECTURAL DESIGN; BIBLIOGRAPHIES; CATEGORIAL DIVERGENCE; Computer Programming and Software; CONFLATIONAL DIVERGENCE; CONTEXTUAL AMBIGUITY; Cybernetics; DEFICIENCIES; DESIGN CRITERIA; EUROPE; HISTORY; HYBRID SYSTEMS; JAPAN; LEXICAL AMBIGUITY; LIMITATIONS; Linguistics; LITERATURE SURVEYS; NEURAL NETS; SEMANTIC AMBIGUITY; SEMANTICS; STRUCTURAL DIVERGENCE; SYNTACTIC AMBIGUITY; SYNTAX; TENSE GENERATION; TEST AND EVALUATION; THEMATIC DIVERGENCE; UNITED STATES
|
|
URL: http://www.dtic.mil/docs/citations/ADA455393
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA455393
|
|
BASE
|
|
Hide details
|
|
|
|
|
