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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] |
Neural Network
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Visual Cortex
The visual cortex of the brain is the area of the cerebral cortex that processes visual information. It is located in the occipital lobe. Sensory input originating from the eyes travels through the lateral geniculate nucleus in the thalamus and then reaches the visual cortex. The area of the visual cortex that receives the sensory input from the lateral geniculate nucleus is the primary visual cortex, also known as visual area 1 ( V1), Brodmann area 17, or the striate cortex. The extrastriate areas consist of visual areas 2, 3, 4, and 5 (also known as V2, V3, V4, and V5, or Brodmann area 18 and all Brodmann area 19). Both hemispheres of the brain include a visual cortex; the visual cortex in the left hemisphere receives signals from the right visual field, and the visual cortex in the right hemisphere receives signals from the left visual field. Introduction The primary visual cortex (V1) is located in and around the calcarine fissure in the occipital lobe. Each hemisphere's V1 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Brown Corpus
The Brown University Standard Corpus of Present-Day American English (or just Brown Corpus) is an electronic collection of text samples of American English, the first major structured corpus of varied genres. This corpus first set the bar for the scientific study of the frequency and distribution of word categories in everyday language use. Compiled by Henry Kučera and W. Nelson Francis at Brown University, in Rhode Island, it is a general language corpus containing 500 samples of English, totaling roughly one million words, compiled from works published in the United States in 1961. History In 1967, Kučera and Francis published their classic work ''Computational Analysis of Present-Day American English'', which provided basic statistics on what is known today simply as the ''Brown Corpus''. The Brown Corpus was a carefully compiled selection of current American English, totalling about a million words drawn from a wide variety of sources. Kučera and Francis subjected it to a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Overfitting
mathematical modeling, overfitting is "the production of an analysis that corresponds too closely or exactly to a particular set of data, and may therefore fail to fit to additional data or predict future observations reliably". An overfitted model is a mathematical model that contains more parameters than can be justified by the data. The essence of overfitting is to have unknowingly extracted some of the residual variation (i.e., the noise) as if that variation represented underlying model structure. Underfitting occurs when a mathematical model cannot adequately capture the underlying structure of the data. An under-fitted model is a model where some parameters or terms that would appear in a correctly specified model are missing. Under-fitting would occur, for example, when fitting a linear model to non-linear data. Such a model will tend to have poor predictive performance. The possibility of over-fitting exists because the criterion used for selecting the model is no ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Today (American TV Program)
''Today'' (also called ''The Today Show'' or informally, ''NBC News Today'') is an American news and talk morning television show that airs weekdays from 7:00 a.m. to 11:00 a.m. on NBC. The program debuted on January 14, 1952. It was the first of its genre on American television and in the world, and after 70 years of broadcasting it is fifth on the list of longest-running United States television series. Originally a weekday two-hour program from 7:00 a.m. to 9:00 a.m., it expanded to Sundays in 1987 and Saturdays in 1992. The weekday broadcast expanded to three hours in 2000, and to four hours in 2007 (though over time, the third and fourth hours became distinct entities). ''Today''s dominance was virtually unchallenged by the other networks until the late 1980s, when it was overtaken by ABC's ''Good Morning America''. ''Today'' retook the Nielsen ratings lead the week of December 11, 1995, and held onto that position for 852 consecutive weeks until the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neuro-linguistic Programming
Neuro-linguistic programming (NLP) is a pseudoscientific approach to communication, personal development and psychotherapy, that first appeared in Richard Bandler and John Grinder's 1975 book ''The Structure of Magic I''. NLP claims that there is a connection between neurological processes (''neuro-''), language (''linguistic'') and acquired behavioral patterns (''programming''), and that these can be changed to achieve specific goals in life. According to Bandler and Grinder, NLP can treat problems such as phobias, depression, tic disorders, psychosomatic illnesses, near-sightedness, allergy, the common cold, and learning disorders,Archived aGhostarchiveand thWayback Machine often in a single session. They also claim that NLP can "model" the skills of exceptional people, allowing anyone to acquire them. NLP has been adopted by some hypnotherapists, as well as by companies that run seminars marketed as " leadership training" to businesses and government agencies. There is ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Neural Network
Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron receives signals then processes them and can signal neurons connected to it. The "signal" at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called ''edges''. Neurons and edges typically have a ''weight'' that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Neurons may have a threshold such that a signal is sent only if the aggregate signal crosses that threshold. Typically ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Phonetic Transcription
Phonetic transcription (also known as phonetic script or phonetic notation) is the visual representation of speech sounds (or ''phones'') by means of symbols. The most common type of phonetic transcription uses a phonetic alphabet, such as the International Phonetic Alphabet. Versus orthography The pronunciation of words in all languages changes over time. However, their written forms (orthography) are often not modified to take account of such changes, and do not accurately represent the pronunciation. Words borrowed from other languages may retain the spelling from the original language, which may have a different system of correspondences between written symbols and speech sounds. Pronunciation can also vary greatly among dialects of a language. Standard orthography in some languages, such as English and Tibetan, is often irregular and makes it difficult to predict pronunciation from spelling. For example, the words ''bough'', ''chough'', ''cough'', ''though'' and ''through' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Backpropagation
In machine learning, backpropagation (backprop, BP) is a widely used algorithm for training feedforward neural network, feedforward artificial neural networks. Generalizations of backpropagation exist for other artificial neural networks (ANNs), and for functions generally. These classes of algorithms are all referred to generically as "backpropagation". In Artificial neural network#Learning, fitting a neural network, backpropagation computes the gradient of the loss function with respect to the Glossary of graph theory terms#weight, weights of the network for a single input–output example, and does so Algorithmic efficiency, efficiently, unlike a naive direct computation of the gradient with respect to each weight individually. This efficiency makes it feasible to use gradient methods for training multilayer networks, updating weights to minimize loss; gradient descent, or variants such as stochastic gradient descent, are commonly used. The backpropagation algorithm works by ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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