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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] |
Speech Recognition
Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the main benefit of searchability. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis. Some speech recognition systems require "training" (also called "enrollment") where an individual speaker reads text or isolated vocabulary into the system. The system analyzes the person's specific voice and uses it to fine-tune the recognition of that person's speech, resulting in increased accuracy. Systems that do not use training are called "speaker-independent" systems. Systems that use training are called "speaker dependent". Speech recognition ... [...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] |
Levenshtein Distance
In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. Informally, the Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other. It is named after the Soviet mathematician Vladimir Levenshtein, who considered this distance in 1965. Levenshtein distance may also be referred to as ''edit distance'', although that term may also denote a larger family of distance metrics known collectively as edit distance. It is closely related to pairwise string alignments. Definition The Levenshtein distance between two strings a, b (of length , a, and , b, respectively) is given by \operatorname(a, b) where : \operatorname(a, b) = \begin , a, & \text , b, = 0, \\ , b, & \text , a, = 0, \\ \operatorname\big(\operatorname(a),\operatorname(b)\big) & \text a = b \\ 1 + \min ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Phoneme
In phonology and linguistics, a phoneme () is a unit of sound that can distinguish one word from another in a particular language. For example, in most dialects of English, with the notable exception of the West Midlands and the north-west of England, the sound patterns (''sin'') and (''sing'') are two separate words that are distinguished by the substitution of one phoneme, , for another phoneme, . Two words like this that differ in meaning through the contrast of a single phoneme form a ''minimal pair''. If, in another language, any two sequences differing only by pronunciation of the final sounds or are perceived as being the same in meaning, then these two sounds are interpreted as phonetic variants of a single phoneme in that language. Phonemes that are established by the use of minimal pairs, such as ''tap'' vs ''tab'' or ''pat'' vs ''bat'', are written between slashes: , . To show pronunciation, linguists use square brackets: (indicating an aspirated ''p'' in ''p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Microsoft Research
Microsoft Research (MSR) is the research subsidiary of Microsoft. It was created in 1991 by Richard Rashid, Bill Gates and Nathan Myhrvold with the intent to advance state-of-the-art computing and solve difficult world problems through technological innovation in collaboration with academic, government, and industry researchers. The Microsoft Research team has more than 1,000 computer scientists, physicists, engineers, and mathematicians, including Turing Award winners, Fields Medal winners, MacArthur Fellows, and Dijkstra Prize winners. Between 2010 and 2018, 154,000 AI patents were filed worldwide, with Microsoft having by far the largest percentage of those patents, at 20%.Louis Columbus, January 6, 201Microsoft Leads The AI Patent Race Going Into 2019 ''Forbes'' According to estimates in trade publications, Microsoft spent about $6 billion annually in research initiatives from 2002-2010 and has spent from $10–14 billion annually since 2010. Microsoft Research has made signi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Syntax
In linguistics, syntax () is the study of how words and morphemes combine to form larger units such as phrases and sentences. Central concerns of syntax include word order, grammatical relations, hierarchical sentence structure ( constituency), agreement, the nature of crosslinguistic variation, and the relationship between form and meaning (semantics). There are numerous approaches to syntax that differ in their central assumptions and goals. Etymology The word ''syntax'' comes from Ancient Greek roots: "coordination", which consists of ''syn'', "together", and ''táxis'', "ordering". Topics The field of syntax contains a number of various topics that a syntactic theory is often designed to handle. The relation between the topics is treated differently in different theories, and some of them may not be considered to be distinct but instead to be derived from one another (i.e. word order can be seen as the result of movement rules derived from grammatical relations). Se ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Edit Distance
In computational linguistics and computer science, edit distance is a string metric, i.e. a way of quantifying how dissimilar two strings (e.g., words) are to one another, that is measured by counting the minimum number of operations required to transform one string into the other. Edit distances find applications in natural language processing, where automatic spelling correction can determine candidate corrections for a misspelled word by selecting words from a dictionary that have a low distance to the word in question. In bioinformatics, it can be used to quantify the similarity of DNA sequences, which can be viewed as strings of the letters A, C, G and T. Different definitions of an edit distance use different sets of string operations. Levenshtein distance operations are the removal, insertion, or substitution of a character in the string. Being the most common metric, the term ''Levenshtein distance'' is often used interchangeably with ''edit distance''. Types of edit dis ... [...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] |
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] |
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] |
