42 results about "Language modelling" patented technology

The invention relates to a target tracking method based on a language building mode twin network, and the method comprises the steps: S1, obtaining a video containing the continuous motion of a target, and making a training data set according to the video; s2, training a twin neural network according to the training data set; s3, keeping parameters of the twin neural network unchanged, and training a target position extraction network; s4, performing joint training on the trained twin neural network and the trained target position extraction network to obtain a language building mode twin network; and S5, acquiring a real-time image of the target to be tracked, and performing real-time tracking on the target to be tracked by using the language modeling twin network. Expert experience knowledge does not need to be integrated into the algorithm, and the implementation process is simpler and more convenient. In addition, the system is high in expansibility and can be connected to a more general intelligent system.

The invention discloses a semantic meaning understanding method fusing semantic information, and belongs to the technical field of language information processing. The problem that an existing language modeling method is high in complexity and cannot give consideration to the effect is solved. The method comprises the following steps of: firstly, processing a language by taking each word as a unitaccording to two paths, wherein the left path is a word encoder + RNN + word decoder, and the output of the left path is recorded as wl; the right path comprises a synonym encoder+RNN + synonym decoder+a word decoder + sigmoid, and the output of the right path is recorded as wr; and then fusing the outputs of the two paths. The method is mainly for language meaning understanding.

The invention discloses a streaming speech recognition system and method based on a non-autoregression model. The method comprises the following steps: S11, extracting an acoustic feature sequence; s12, generating an acoustic coding state sequence; s13, generating an acoustic coding state sequence; s14, CTC output probability distribution and connection time sequence loss are calculated; s15, performing alignment by using a viterbi algorithm; s16, inputting section by section and calculating joint cross entropy loss; s17, calculating a gradient according to the joint loss of the joint time sequence loss and the joint cross entropy loss, and carrying out back propagation; s18, circularly executing the steps S12 to S17 until the training is completed; the system comprises an acoustic feature sequence extraction module, a streaming acoustic encoder, a CTC linear transformation layer and a non-autoregressive decoder which are sequentially connected with one another. According to the invention, non-autoregressive decoding is carried out on the input audio segments segment by segment, so that the streaming reasoning speed is improved. And the loss of the language modeling capability is avoided.

The present invention relates to an improved artificial neural network for predicting one or more next items in a sequence of items based on an input sequence item. The artificial neural network is implemented on an electronic device comprising a processor, and at least one input interface configured to receive one or more input sequence items, wherein the processor is configured to implement theartificial neural network and generate one or more predicted next items in a sequence of items using the artificial neural network by providing an input sequence item received at the at least one input interface and a side input as inputs to the artificial neural network, wherein the side input is configured to maintain a record of input sequence items received at the input interface.

The invention provides an SIMSCRIPT language-oriented discrete event simulation graphical modeling method, which comprises the following steps of: adding entities, routines, events and other primitives into a canvas serving as a primitive bearing container in a dragging manner according to entity flow graphs, activity cycle graphs and other modeling technologies, and representing an interaction relationship among the entities, the routines and the events through connecting lines, according to the method, primitives can be drawn and managed in the canvases, the canvases can be divided into a plurality of canvases according to the calling relation and the hierarchical relation, all the canvases can be stored as engineering files of specific formats, and the engineering files can automatically generate SIMSCRIPT simulation codes according to mapping rules. The discrete event simulation program is built based on the SIMSCRIPT simulation language and a graphical dragging mode, the problem that SIMSCRIPT grammar and manual code writing need to be familiar with when SIMSCRIPT language modeling is adopted is solved, the modeling process can be clear and visual, model reuse is simpler, thelearning cost is lower, user groups are wider, and communication between domain experts and modeling personnel is facilitated.

The invention refers to a natural language processing system configured for receiving an input sequence ci of input words representing a first sequence of words in a natural language of a first text and generating an output sequence of output words representing a second sequence of words in a natural language of a second text and modeled by a multinominal topic model, wherein the multinominal topic model is extended by an incorporation of full contextual information around each word vi, wherein both preceding words vi around each word vi are captured by using a bi-directional language modelling and a feed-forward fashion, wherein position dependent forward hidden layers {right arrow over (h)}i and backward hidden layers i for each word vi are computed.