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NIST (metric)
NIST is a method for evaluation of machine translation, evaluating the quality of text which has been translated using machine translation. Its name comes from the US National Institute of Standards and Technology. It is based on the Bilingual evaluation understudy, BLEU metric, but with some alterations. Where Bilingual evaluation understudy, BLEU simply calculates n-gram precision adding equal weight to each one, NIST also calculates how informative a particular n-gram is. That is to say when a correct n-gram is found, the rarer that n-gram is, the more weight it will be given. For example, if the bigram "on the" is correctly matched, it will receive lower weight than the correct matching of bigram "interesting calculations", as this is less likely to occur. NIST also differs from Bilingual evaluation understudy, BLEU in its calculation of the brevity penalty insofar as small variations in translation length do not impact the overall score as much. See also * BLEU * F1 score, F ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Evaluation Of Machine Translation
Various methods for the evaluation for machine translation have been employed. This article focuses on the evaluation of the output of machine translation, rather than on performance or usability evaluation. Round-trip translation A typical way for lay people to assess machine translation quality is to translate from a source language to a target language and back to the source language with the same engine. Though intuitively this may seem like a good method of evaluation, it has been shown that round-trip translation is a "poor predictor of quality". The reason why it is such a poor predictor of quality is reasonably intuitive. A round-trip translation is not testing one system, but two systems: the language pair of the engine for translating ''into'' the target language, and the language pair translating ''back from'' the target language. Consider the following examples of round-trip translation performed from English to Italian and Portuguese from Somers (2005): : : In the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Translation
Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation or interactive translation), is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another. On a basic level, MT performs mechanical substitution of words in one language for words in another, but that alone rarely produces a good translation because recognition of whole phrases and their closest counterparts in the target language is needed. Not all words in one language have equivalent words in another language, and many words have more than one meaning. Solving this problem with corpus statistical and neural techniques is a rapidly growing field that is leading to better translations, handling differences in linguistic typology, translation of idioms, and the isolation of anomalies. Current machine translation software often allows for customizat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
National Institute Of Standards And Technology
The National Institute of Standards and Technology (NIST) is an agency of the United States Department of Commerce whose mission is to promote American innovation and industrial competitiveness. NIST's activities are organized into physical science laboratory programs that include nanoscale science and technology, engineering, information technology, neutron research, material measurement, and physical measurement. From 1901 to 1988, the agency was named the National Bureau of Standards. History Background The Articles of Confederation, ratified by the colonies in 1781, provided: The United States in Congress assembled shall also have the sole and exclusive right and power of regulating the alloy and value of coin struck by their own authority, or by that of the respective states—fixing the standards of weights and measures throughout the United States. Article 1, section 8, of the Constitution of the United States, ratified in 1789, granted these powers to the new Congr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bilingual Evaluation Understudy
Bleu or BLEU may refer to: * the French word for blue * '' Three Colors: Blue'', a 1993 movie * BLEU (Bilingual Evaluation Understudy), a machine translation evaluation metric * Belgium–Luxembourg Economic Union * Blue cheese, a type of cheese * Parti bleu, 19th century political group in Quebec, Canada * ''Bleu'' (blue-rare), synonymous with "extra rare", indicating a barely-cooked meat preparation; very red and cold * ''Le Bleu'' (2001 album) album by Justin King People * Bleu (musician), a member of pop-group L.E.O. * Corbin Bleu, an American actor, model, dancer and vocalist * Deis, a character from the ''Breath of Fire'' role-playing videogame series who is known as "Bleu" in the English versions See also * Blue (other) * Lebleu (other) * Les Bleus (other) Les Bleus may refer to: National team of France ''Les Bleus'' (French for "The Blues") is often used in a French sporting context, and in particular may refer to: * France's national team: * ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
N-gram
In the fields of computational linguistics and probability, an ''n''-gram (sometimes also called Q-gram) is a contiguous sequence of ''n'' items from a given sample of text or speech. The items can be phonemes, syllables, letters, words or base pairs according to the application. The ''n''-grams typically are collected from a text or speech corpus. When the items are words, -grams may also be called ''shingles''. Using Latin numerical prefixes, an ''n''-gram of size 1 is referred to as a "unigram"; size 2 is a "bigram" (or, less commonly, a "digram"); size 3 is a "trigram". English cardinal numbers are sometimes used, e.g., "four-gram", "five-gram", and so on. In computational biology, a polymer or oligomer of a known size is called a ''k''-mer instead of an ''n''-gram, with specific names using Greek numerical prefixes such as "monomer", "dimer", "trimer", "tetramer", "pentamer", etc., or English cardinal numbers, "one-mer", "two-mer", "three-mer", etc. Applications ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
BLEU
Bleu or BLEU may refer to: * the French word for blue * '' Three Colors: Blue'', a 1993 movie * BLEU (Bilingual Evaluation Understudy), a machine translation evaluation metric * Belgium–Luxembourg Economic Union * Blue cheese, a type of cheese * Parti bleu, 19th century political group in Quebec, Canada * ''Bleu'' (blue-rare), synonymous with "extra rare", indicating a barely-cooked meat preparation; very red and cold * ''Le Bleu'' (2001 album) album by Justin King People * Bleu (musician), a member of pop-group L.E.O. * Corbin Bleu, an American actor, model, dancer and vocalist * Deis, a character from the ''Breath of Fire'' role-playing videogame series who is known as "Bleu" in the English versions See also * Blue (other) * Lebleu (other) * Les Bleus (other) Les Bleus may refer to: National team of France ''Les Bleus'' (French for "The Blues") is often used in a French sporting context, and in particular may refer to: * France's national team: ** ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
F1 Score
In statistical analysis of binary classification, the F-score or F-measure is a measure of a test's accuracy. It is calculated from the precision and recall of the test, where the precision is the number of true positive results divided by the number of all positive results, including those not identified correctly, and the recall is the number of true positive results divided by the number of all samples that should have been identified as positive. Precision is also known as positive predictive value, and recall is also known as sensitivity in diagnostic binary classification. The F1 score is the harmonic mean of the precision and recall. The more generic F_\beta score applies additional weights, valuing one of precision or recall more than the other. The highest possible value of an F-score is 1.0, indicating perfect precision and recall, and the lowest possible value is 0, if either precision or recall are zero. Etymology The name F-measure is believed to be named after ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
METEOR
A meteoroid () is a small rocky or metallic body in outer space. Meteoroids are defined as objects significantly smaller than asteroids, ranging in size from grains to objects up to a meter wide. Objects smaller than this are classified as micrometeoroids or space dust. Most are fragments from comets or asteroids, whereas others are collision impact debris ejected from bodies such as the Moon or Mars. When a meteoroid, comet, or asteroid enters Earth's atmosphere at a speed typically in excess of , aerodynamic heating of that object produces a streak of light, both from the glowing object and the trail of glowing particles that it leaves in its wake. This phenomenon is called a meteor or "shooting star". Meteors typically become visible when they are about 100 km above sea level. A series of many meteors appearing seconds or minutes apart and appearing to originate from the same fixed point in the sky is called a meteor shower. A meteorite is the remains of a meteoroid th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Phrase Chunking
Phrase chunking is a phase of natural language processing that separates and segments a sentence into its subconstituents, such as noun, verb, and prepositional phrases, abbreviated as NP, VP, and PP, respectively. Typically, each subconstituent or chunk is denoted by brackets.Erik F. Tjong Kim Sang and Sabine Buchholz. 2000. Introduction to the conll-2000 shared task: chunking. In ''Proceedings of the 2nd workshop on Learning language in logic and the 4th CONLL'', pages 127–132, Morristown, NJ, USA. Association for Computational Linguistics. See also *Terminology extraction *Part-of-speech tagging *Constituent (linguistics) In syntactic analysis, a constituent is a word or a group of words that function as a single unit within a hierarchical structure. The constituent structure of sentences is identified using ''tests for constituents''. These tests apply to a portio ... External linksTermExtractor [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ROUGE (metric)
ROUGE, or Recall-Oriented Understudy for Gisting Evaluation, is a set of metrics and a software package used for evaluating automatic summarization and machine translation software in natural language processing. The metrics compare an automatically produced summary or translation against a reference or a set of references (human-produced) summary or translation. Metrics The following five evaluation metrics are available. *ROUGE-N: Overlap of n-grams between the system and reference summaries. **ROUGE-1 refers to the overlap of ''unigram'' ''(each word)'' between the system and reference summaries. **ROUGE-2 refers to the overlap of ''bigrams'' between the system and reference summaries. *ROUGE-L: Longest Common Subsequence (LCS) based statistics. Longest common subsequence problem takes into account sentence level structure similarity naturally and identifies longest co-occurring in sequence n-grams automatically. *ROUGE-W: Weighted LCS-based statistics that favors consecutive L ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Word Error Rate
Word error rate (WER) is a common metric of the performance of a speech recognition or machine translation system. The general difficulty of measuring performance lies in the fact that the recognized word sequence can have a different length from the reference word sequence (supposedly the correct one). The WER is derived from the Levenshtein distance, working at the word level instead of the phoneme level. The WER is a valuable tool for comparing different systems as well as for evaluating improvements within one system. This kind of measurement, however, provides no details on the nature of translation errors and further work is therefore required to identify the main source(s) of error and to focus any research effort. This problem is solved by first aligning the recognized word sequence with the reference (spoken) word sequence using dynamic string alignment. Examination of this issue is seen through a theory called the power law that states the correlation between perplexity an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
