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Recurrent Neural Network
A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes can create a cycle, allowing output from some nodes to affect subsequent input to the same nodes. This allows it to exhibit temporal dynamic behavior. Derived from feedforward neural networks, RNNs can use their internal state (memory) to process variable length sequences of inputs. This makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition. Recurrent neural networks are theoretically Turing complete and can run arbitrary programs to process arbitrary sequences of inputs. The term "recurrent neural network" is used to refer to the class of networks with an infinite impulse response, whereas "convolutional neural network" refers to the class of finite impulse response. Both classes of networks exhibit temporal dynamic behavior. A finite impulse recurrent network is a directed acyclic graph that can be unrolled and replace ... [...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] |
Long Short-term Memory
Long short-term memory (LSTM) is an artificial neural network used in the fields of artificial intelligence and deep learning. Unlike standard feedforward neural networks, LSTM has feedback connections. Such a recurrent neural network (RNN) can process not only single data points (such as images), but also entire sequences of data (such as speech or video). For example, LSTM is applicable to tasks such as unsegmented, connected handwriting recognition, speech recognition, machine translation, robot control, video games, and healthcare. The name of LSTM refers to the analogy that a standard RNN has both "long-term memory" and "short-term memory". The connection weights and biases in the network change once per episode of training, analogous to how physiological changes in synaptic strengths store long-term memories; the activation patterns in the network change once per time-step, analogous to how the moment-to-moment change in electric firing patterns in the brain store short- ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Learning Rule
An artificial neural network's learning rule or learning process is a method, mathematical logic or algorithm which improves the network's performance and/or training time. Usually, this rule is applied repeatedly over the network. It is done by updating the weights and bias levels of a network when a network is simulated in a specific data environment. A learning rule may accept existing conditions (weights and biases) of the network and will compare the expected result and actual result of the network to give new and improved values for weights and bias. Depending on the complexity of actual model being simulated, the learning rule of the network can be as simple as an XOR gate or mean squared error, or as complex as the result of a system of differential equations. The learning rule is one of the factors which decides how fast or how accurately the artificial network can be developed. Depending upon the process to develop the network there are three main models of machine le ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Jeff Elman
Jeffrey Locke Elman (January 22, 1948 – June 28, 2018) was an American psycholinguist and professor of cognitive science at the University of California, San Diego (UCSD). He specialized in the field of neural networks. In 1990, he introduced the simple recurrent neural network (SRNN), also known as the 'Elman network', which is capable of processing sequentially ordered stimuli, and has since become widely used. Elman's work was highly significant to our understanding of how languages are acquired and also, once acquired, how sentences are comprehended. Sentences in natural languages are composed of sequences of words that are organized in phrases and hierarchical structures. The Elman network provides an important hypothesis for how neural networks—and, by analogy, the human brain—might be doing the learning and processing of such structures.Jeffrey L. Elman. Finding structure in time. ''Cognitive Science'', Volume 14, Issue 2, Pages 179-211, 1990 Early life Elman att ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Elman Srnn , a surname
{{disambiguation ...
Elman may refer to: * El Maan, a town in south-central Somalia * Elman FC, a Somali football club * Elman (name) See also * Ellman Ellman is a surname. Notable people with the surname include: *John Ellman, agriculturalist of Glynde who developed the Southdown breed of sheep *Louise Ellman, British politician *Mark Ellman, see Maui Tacos *Michael Ellman Dutch economist See al ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recurrent Neural Network Unfold
Recurrence and recurrent may refer to: *''Disease recurrence'', also called relapse *''Eternal recurrence'', or eternal return, the concept that the universe has been recurring, and will continue to recur, in a self-similar form an infinite number of times across infinite time or space *Historic recurrence, the repetition of similar events in history * Poincaré recurrence theorem, Henri Poincaré's theorem on dynamical systems *Radial recurrent artery – arising from the radial artery immediately below the elbow *Recursive definition *Recurrent neural network, a special artificial neural network *Recurrence period density entropy, an information-theoretic method for summarising the recurrence properties of dynamical systems *Recurrence plot, a statistical plot that shows a pattern that re-occurs *Recurrence relation, an equation which defines a sequence recursively *Recurrent rotation, a term used in contemporary hit radio for frequently aired songs *''Recurrence'' The Railway Chi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Automatic Image Captioning
Natural language generation (NLG) is a software process that produces natural language output. In one of the most widely-cited survey of NLG methods, NLG is characterized as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems than can produce understandable texts in English or other human languages from some underlying non-linguistic representation of information". While it is widely agreed that the output of any NLG process is text, there is some disagreement on whether the inputs of an NLG system need to be non-linguistic. Common applications of NLG methods include the production of various reports, for example weather and patient reports; image captions; and chatbots. Automated NLG can be compared to the process humans use when they turn ideas into writing or speech. Psycholinguists prefer the term language production for this process, which can also be described in mathematical terms, or modeled i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Language Modeling
A language model is a probability distribution over sequences of words. Given any sequence of words of length , a language model assigns a probability P(w_1,\ldots,w_m) to the whole sequence. Language models generate probabilities by training on text corpora in one or many languages. Given that languages can be used to express an infinite variety of valid sentences (the property of digital infinity), language modeling faces the problem of assigning non-zero probabilities to linguistically valid sequences that may never be encountered in the training data. Several modelling approaches have been designed to surmount this problem, such as applying the Markov assumption or using neural architectures such as recurrent neural networks or transformers. Language models are useful for a variety of problems in computational linguistics; from initial applications in speech recognition to ensure nonsensical (i.e. low-probability) word sequences are not predicted, to wider use in machine t ... [...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] |
Google Android
Android is a mobile operating system based on a modified version of the Linux kernel and other open-source software, designed primarily for touchscreen mobile devices such as smartphones and tablets. Android is developed by a consortium of developers known as the Open Handset Alliance and commercially sponsored by Google. It was unveiled in November 2007, with the first commercial Android device, the HTC Dream, being launched in September 2008. Most versions of Android are proprietary. The core components are taken from the Android Open Source Project (AOSP), which is free and open-source software (FOSS) primarily licensed under the Apache License. When Android is installed on devices, the ability to modify the otherwise free and open-source software is usually restricted, either by not providing the corresponding source code or by preventing reinstallation through technical measures, thus rendering the installed version proprietary. Most Android devices ship with additional ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text-to-speech
Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech. The reverse process is speech recognition. Synthesized speech can be created by concatenating pieces of recorded speech that are stored in a database. Systems differ in the size of the stored speech units; a system that stores phones or diphones provides the largest output range, but may lack clarity. For specific usage domains, the storage of entire words or sentences allows for high-quality output. Alternatively, a synthesizer can incorporate a model of the vocal tract and other human voice characteristics to create a completely "synthetic" voice output. The quality of a speech synthesizer is judged by its similarity to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Baidu
Baidu, Inc. ( ; , meaning "hundred times") is a Chinese multinational technology company specializing in Internet-related services and products and artificial intelligence (AI), headquartered in Beijing's Haidian District. It is one of the largest AI and Internet companies in the world. The holding company of the group is incorporated in the Cayman Islands. Baidu was incorporated in January 2000 by Robin Li and Eric Xu. The Baidu search engine is currently the sixth largest website in the Alexa Internet rankings. Baidu has origins in RankDex, an earlier search engine developed by Robin Li in 1996, before he founded Baidu in 2000. Baidu offers various services, including a Chinese search engine, as well as a mapping service called Baidu Maps. Baidu offers about 57 search and community services, such as Baidu Baike (an online encyclopedia), Baidu Wangpan (a cloud storage service), and Baidu Tieba (a keyword-based discussion forum). Baidu Global Business Unit (GBU) is respo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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