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95 results about "Expressed emotion" patented technology

Expressed emotion (EE), is a measure of the family environment that is based on how the relatives of a psychiatric patient spontaneously talk about the patient. It is a psychological term specifically applied to psychiatric patients, and differs greatly from the daily use of the phrase "emotion expression" or another psychological concept "family expressiveness"; frequent communication and natural expression of emotion among family members is a conducive, healthy habit.

Method for establishing large-scale cross-field text emotion orientation analysis framework

ActiveCN106096004AImprove robustnessSolve the problem of being stuck in a local optimumData miningSpecial data processing applicationsLocal optimumAlgorithm
The invention discloses a method for establishing a large-scale cross-field text emotion orientation analysis framework. The method comprises the steps that precise word segmentation is carried out on sample documents in a source field and sample documents in a target field to form two word vector tables; word vectors are clustered, and the fields are aligned; primary sentence modeling is carried out on calibration samples in the source field through the word vectors and serves as input of DCELM, and interlayer abstraction features of text vectors are extracted through convolution operation; convolution layer parameters obtained when the classification effect of a verification set is best are recorded and serve as parameters of a DCELM network convolution layer; finally, interlayer abstraction features of calibration samples, extracted through DCNN, of a small number of target fields are used for training implicit layer parameters of a classifier ELM to establish the large-scale cross-field text emotion orientation analysis framework. By means of the technical scheme, the difference of words for expressing emotion polarities among the fields is eliminated on the sample layer, the defects that on a full-connection layer, local optimization is easily caused and the generalization ability is weak are effectively solved, and the anti-interference performance of a model is improved.
Owner:河北广潮科技有限公司

Graph-text mixed typesetting method and device, computer readable storage medium and terminal

PendingCN108805960ARich contextIn line with the habit of expressing emotionEditing/combining figures or textAmbiguityComputer terminal
The invention discloses a graph-text mixed typesetting method and device, a computer readable storage medium and a terminal. The graph-text mixed typesetting method comprises the following steps: acquiring user data; parsing the user data through a preset expression mapping table; constructing expression metadata based on a parsing result, wherein the expression metadata comprise character data and an expression placeholder character, wherein the expression placeholder character is used for identifying a to-be-displayed expression picture, and the attribute of the expression placeholder character is set as the attribute of the to-be-displayed expression picture; and performing graph-text rendering on the expression metadata according to a preset layout rule. According to the graph-text mixed typesetting method provided by the embodiment of the invention, the technical problem of how to improve the visual experience of a user is solved, and the context of user comments is enriched, which is easier to read than simple characters, can avoid the ambiguity of saying nothing, and can determine the expression picture corresponding to an emotional element; and besides, the graph-text mixedtypesetting method conforms to the habit of expressing emotions by the user, and improves the interaction amount and activity of the user in a comment area.
Owner:BEIJING BYTEDANCE NETWORK TECH CO LTD

Hotel emotion dictionary establishment method, comment emotion analysis method and system

InactiveCN107203520AOvercoming the inadequacy of only knowing whether reviews are generally positive or negativeSemantic analysisSpecial data processing applicationsPattern recognitionExpressed emotion
The invention provides a hotel emotion dictionary establishment method, comment emotion analysis method and system. The hotel emotion dictionary establishment method, comment emotion analysis method and system comprise establishment of a hotel custom-made emotion dictionary, a network term emotion dictionary, a privative word dictionary and a degree adverb dictionary, wherein the hotel custom-made emotion dictionary is used for grabbing customer network comments about a hotel, extracting adjectives and/ or adverbs from the network comments as candidate words, preserving candidate words not included in a preset basic emotion dictionary, selecting at least one positive candidate word to form a positive basic standard word collection and at least one negative candidate word to form a negative basic standard word collection from the non-included candidate words, and determining and storing the custom-made positive or negative property of the candidate words according to the positive basic standard word collection and the negative basic standard word collection; the network term emotion dictionary is used for collecting and storing non-included positive network popular words and negative network popular words, which are used for expressing emotion, in the preset basic emotion dictionary; the privative word dictionary is used for collecting and storing privative words, and the degree adverb dictionary is used for collecting and storing adverbs of degree. The hotel emotion dictionary establishment method, comment emotion analysis method and system can provide strong technical support for the emotion analysis of the hotel network comments.
Owner:SHANGHAI ADVANCED RES INST CHINESE ACADEMY OF SCI

Voice annotation method for Chinese speech emotion database combined with electroglottography

The invention provides a voice annotation method for a Chinese speech emotion database combined with an electroglottography. The main annotation content of the voice annotation method comprises eight layers of information which are simultaneously annotated on each voice. The eight layers of information comprises that a first layer is a text conversion layer, speaking content of a speaker and corresponding paralanguage information are made clear; a second layer is a syllable layer, a regular spell and a tone of each syllable are annotated; a third layer is an initial / final consonant layer, initial / final consonants of the syllable layer are annotated separately, and meanwhile tone information is marked; a fourth layer is an unvoiced sound, voiced sound and silence layer, and unvoiced sounds, voiced sounds and silences of the voices are segmented combined with the electroglottography; a fifth layer is a paralanguage information layer, and paralanguage information included in each voice is annotated; a sixth layer is an emotion layer, and according to emotion status which is expressed by the speaker, each voice is annotated with information comprising seven kinds of emotions and expression degrees of each kind of the emotions; a seventh layer is a stress index layer, and intensity information of pronunciation of each voice is annotated; an eighth layer is a statement function layer, and a statement type of each statement is annotated.
Owner:BEIHANG UNIV

Language text processing method and device and storage medium

The invention discloses a language text processing method and device and a storage medium, which are used for improving the accuracy of the emotion polarity analysis result expressed by the language text. The language text processing method comprises the following steps: obtaining the language text to be processed; Word segmentation is performed on the language text to be processed to obtain a first word segmentation object, including words obtained by word segmentation and corresponding phonetic alphabet; in accordance with the result of word segmentation, utilizing a vector conversion modelto convert the first word segmentation object into a first word segmentation object vector, the vector conversion model being obtained by training the first word segmentation object contained in the first sample data according to the distance between the first word segmentation object in the first sample data and the affective polarity label of the first word segmentation object; and according tothe first word segmentation object vector, utilizing the emotion polarity prediction model to predict the corresponding emotion polarity type of the language text to be processed, the emotion polarityprediction model being obtained by using the second sample data with emotion polarity labels.
Owner:TENCENT TECH (SHENZHEN) CO LTD
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