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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 WER metric typically ranges from 0 to 1, where 0 indicates that the compared pieces of text are exactly identical, and 1 (or larger) indicates that they are completely different with no similarity. This way, a WER of 0.8 means that there is an 80% error rate for compared sentences. 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 focu ... [...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. 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 applications include voice user interfaces ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
BLEU
Bleu or BLEU may refer to: * '' Three Colors: Blue'', a 1993 film * 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'', a 2001 album by Justin King People * Bleu (musician), a member of the pop group L.E.O. * Corbin Bleu, an American actor, model, dancer and singer * Yung Bleu, an American record producer, rapper and singer also known as "Bleu" * Deis, a character from the '' Breath of Fire'' role-playing video game series known as "Bleu" in the English versions See also * Blue (other) Blue is a color. Blue may also refer to: Places * Blue, Arizona, an unincorporated community in the United States * Blue, Oklahoma, an unincorporated community in the United States * Blue, W ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Translation
Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical. These methods have since been superseded by neural machine translation and large language models. History Origins The origins of machine translation can be traced back to the work of Al-Kindi, a ninth-century Arabic cryptographer who developed techniques for systemic language translation, including cryptanalysis, frequency analysis, and probability and statistics, which are used in modern machine translation. The idea of machine translation later appeared in the 17th century. In 1629, René Descartes proposed a universal language, with equivalent ideas in different tongues sharing one symbol. The idea of using digital computers for translation of natural languages was proposed as early as 1947 by England's A. D. Booth and Warr ... [...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. 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 applications include voice user interfaces ... [...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. ROUGE metrics range between 0 and 1, with higher scores indicating higher similarity between the automatically produced summary and the reference. 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 ''unigrams'' ''(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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
NIST (metric)
NIST is a method for 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 BLEU metric, but with some alterations. Where 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 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 * F-Measure * METEOR A meteor, known colloquially as a shooting star, is a glowing streak of a small body (usually meteoroid) going ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
METEOR
A meteor, known colloquially as a shooting star, is a glowing streak of a small body (usually meteoroid) going through Earth's atmosphere, after being heated to incandescence by collisions with air molecules in the upper atmosphere, creating a streak of light via its rapid motion and sometimes also by shedding glowing material in its wake. Although a meteor may seem to be a few thousand feet from the Earth, meteors typically occur in the mesosphere at altitudes from . The root word ''meteor'' comes from the Ancient Greek, Greek ''meteōros'', meaning "high in the air". Millions of meteors occur in Earth's atmosphere daily. Most meteoroids that cause meteors are about the size of a grain of sand, i.e. they are usually millimeter-sized or smaller. Meteoroid sizes can be calculated from their mass and density which, in turn, can be estimated from the observed meteor trajectory in the upper atmosphere. Meteors may occur in meteor shower, showers, which arise when Earth passes throu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
F1 Score
In statistical analysis of binary classification and information retrieval systems, the F-score or F-measure is a measure of predictive performance. 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 samples predicted to be positive, 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. It thus symmetrically represents both precision and recall in one metric. 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 ... [...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 String (computing), 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 Spell checker, 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 like 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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Translation
Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical. These methods have since been superseded by neural machine translation and large language models. History Origins The origins of machine translation can be traced back to the work of Al-Kindi, a ninth-century Arabic cryptographer who developed techniques for systemic language translation, including cryptanalysis, frequency analysis, and probability and statistics, which are used in modern machine translation. The idea of machine translation later appeared in the 17th century. In 1629, René Descartes proposed a universal language, with equivalent ideas in different tongues sharing one symbol. The idea of using digital computers for translation of natural languages was proposed as early as 1947 by England's A. D. Booth and Warr ... [...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). Diverse approaches, such as generative grammar and functional grammar, offer unique perspectives on syntax, reflecting its complexity and centrality to understanding human language. Etymology The word ''syntax'' comes from the ancient Greek word , meaning an orderly or systematic arrangement, which consists of (''syn-'', "together" or "alike"), and (''táxis'', "arrangement"). In Hellenistic Greek, this also specifically developed a use referring to the grammatical order of words, with a slightly altered spelling: . The English term, which first appeared in 1548, is partly borrowed from Latin () and Greek, though the L ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Word Recognition
Word recognition, according to Literacy Information and Communication System (LINCS) is "the ability of a reader to recognize written words correctly and virtually effortlessly". It is sometimes referred to as "isolated word recognition" because it involves a reader's ability to recognize words individually from a list without needing similar words for context (language use), contextual help. LINCS continues to say that "rapid and effortless word recognition is the main component of fluent reading" and explains that these skills can be improved by "practic[ing] with flashcards, lists, and word grids". In her 1990 review of the science of learning to read, psychologist Marilyn Jager Adams wrote that "the single immutable and nonoptional fact about skilful reading is that it involves relatively complete processing of the individual letters of print." The article "The Science of Word Recognition" says that "evidence from the last 20 years of work in cognitive psychology indicates tha ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
