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Language and Machines: Computers in Translation and Linguistics (1966)

Page
76
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Page
76
Front Matter (R1-R11)
Contents (R12-R14)
Human Translation (1-1)
Types of Translator Employment (2-3)
English as the Language of Science (4-4)
Time Required for Scientists to Learn Russian (5-5)
Translation in the United States Government (6-6)
Number of Government Translators (7-8)
Amount Spent for Translation (9-10)
Is there a Shortage of Translators or Translation? (11-12)
Regarding a Possible Excess of Translation (13-15)
The Crucial Problems of Translation (16-18)
The Present State of Machine Translation (19-24)
Machine-Aided Translation at Mannheim and Luxembourg (25-28)
Automatic Language Processing and Computational Linguistics (29-31)
Avenues to Improvement of Translation (32-33)
Recommendations (34-34)
Appendix 1. Experiments in Sight Translation and Full Translation (35-36)
Appendix 2. Defense Language Institute Course in Scientific Russian (37-38)
Appendix 3. The Joint Publications Research Service (39-40)
Appendix 4. Public Law 480 Translations (41-42)
Appendix 5. Machine Translations at the Foreign Technology Division, U.S. Air Force Systems Command (43-44)
Appendix 6. Journals Translated with Support by the National Science Foundation (45-49)
Appendix 7. Civil Service Commission Data on Federal Translators (50-53)
Appendix 8. Demand for and Availability of Translators (54-56)
Appendix 9. Cost Estimates of Various Types of Translation (57-66)
Appendix 10. An Experiment in Evaluating the Quality of Translations (67-75)
Appendix 11. Types of Errors Common in Machine Translation (76-78)
Appendix 12. Machine-Aided Translation at the Federal Armed Forces Translation Agency, Mannheim, Germany (79-86)
Appendix 13. Machine-Aided Translation at the European Coal and Steel Community, Luxembourg (87-90)
Appendix 14. Translation Versus Postediting of Machine Translation (91-101)
Appendix 15. Evaluation by Science Editors and Joint Publications Research Service and Foreign Technology Division Translations (102-106)
Appendix 16. Government Support of Machine-Translation Research (107-112)
Appendix 17. Computerized Publishing (113-117)
Appedix 18. Relation Between Programming Languages and Linguistics (118-120)
Appendix 19. Machine Translation and Linguistics (121-123)
Appendix 20. Persons Who Appeared Before the Committee (124-124)

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OCR for page 76
Appendix 11 Types of Errors Common in Machine Translation Two studies have recently been made of the types of errors made in mechanical translation. The first study was very kindly made available to the Committee by the IBM Thomas J. Watson Research Center, Yorktown Heights, New York. By counting and classifying the corrections made by posteditors, this study determined the types and frequency of errors found in the output of four machine translations (Russian to English). GENERAL CLASSIFICATION AND PERCENTAGE OF ERRORS OF ARTICLE I Total number of words: Transliterated words Multiple meddlings and ambiguities Word order rearranged Miscellaneous insertions and corrections Total No. 96 23 45 164 GENERAL CLASSIFICATION AND PERCENTAGE OF ERRORS OF ARTICLE II Total number of words: Transliterated words Multiple meanings and ambiguities Word order rearranged Miscellaneous insertions and corrections Total 76 Approximately 1,200 % 8.0 2.0 3.6 13.6 Approximately 1,200 No. 6 132 17 77 232 % 0.5 11.0 1.4 6.4 19.3

OCR for page 77
GENERAL C LASSIFICATION AND P ERCENTAGE OF ERRORS OF ARTICLE III Total number of words: Transliterated words Multiple meanings and ambiguities Word order rearranged Miscellaneous insertions and corrections Total No. 17 143 36 122 318 GENERAL CLASSIFICATION AND PERCENTAGE OF ERRORS OF ARTICLE IV Total number of words (including individual digits and symbols in all formulas): Transliterated words Multiple meanings and ambiguities No. 1 87 Word order rearranged 14 Miscellaneous insertions and corrections 436 Total 538 Approximately 1,700 l 9 2 7 19 Approximately 1,600 % 5.8 0.9 29.0 35.7 The second study was made by Arthur D. Little, Inc., and was done in a manner similar to the IBM study. That is, machine trarts- lation output was postedited and the errors classified and counted. From the study, the A. D. Little group was able to tell the percent- age of total corrections made in each category. The original con- sisted of approximately 200 pages of scientific Russian. One set of approximately 100 pages was edited by two different editors. The second set contained "approximately 100 pages from seven MT articles edited by at least four different editors."* *An Evaluation of Machine-Aided Translation Activities at F.T.D., Contract AP 33~657~-13616, Case 66556, May 1, 1965, p. ~10. 77

OCR for page 78
PERCENTAGE OF TOTAL CORRECTIONS COUNTED* Error Word omission A. Articles B. Others Wrong words A. Prepositions B. Verb tense, voice, suffix C. Others Russian left in Choice A. Choice of two B. Choice of two, both wrong Unnecessary word Symbol Phrase not interpreted Word order Total Number of Corrections: 7,573 78 % 18.76 15.98 34.74 3.78 5.56 16.24 25.58 4.48 8.17 3.57 11.74 3.09 4.5 3.14 12.73

Representative terms from entire chapter:

order rearranged