Abstract: A first content and a second content of a first user are obtained. The second content is configured by the first user to be displayed to a second user instead of the first content. A familiarity degree between the first user and the second user are determined. A third content is generated based on the first content, the second content, and the familiarity degree. The third content is displayed to the second user.

Abstract: A method, system, and computer program product for recommending an initial database security model. The method may include identifying a plurality of nodes connected to a security network. The method may also include analyzing security characteristics of each node of the plurality of nodes. The method may also include identifying, from the security characteristics, key factors for each node. The method may also include calculating similarities between each node of the plurality of nodes. The method may also include building a self-organized centerless network across the plurality of nodes by grouping nodes with high similarities based on the similarities between each node, where the self-organized centerless network is a centerless network without a central management server, and includes groups of nodes from the plurality of nodes. The method may also include generating federated security models for the groups of nodes.

Abstract: A computer-implemented method to inject security semantics into database queries. The method includes receiving, by a database system, a query, wherein the query is received from a host and the query is generated by a first user account. The method also includes, generating an access plan for the query. The method further includes, determining a first portion of the access plan matches a first security syntax. The method includes, injecting, in response to determining the first portion of the access plan matches the first security syntax, the first security syntax into the access plan. The method further includes, executing the query. The method includes, returning a set of results of the query to the host.

Abstract: A first content and a second content of a first user are obtained. The second content is configured by the first user to be displayed to a second user instead of the first content. A familiarity degree between the first user and the second user are determined. A third content is generated based on the first content, the second content, and the familiarity degree. The third content is displayed to the second user.

Abstract: A method, a device and a computer program product for content collaboration are proposed. One or more computer processors determine voice identification information of a first user based on a voice input from the first user. The one or more computer processors determine a focus for the first user based on the voice identification information, the focus for the first user associated with first content appearing on a screen of the first user. The one or more computer processors set a focus for a second user to be same as the focus for the first user, the focus for the second user associated with second content displayed on a screen of the second user.

Abstract: A computer-implemented method and system for speech recognition of a user speech input. A web page is retrieved from the Internet so that words from the web page may be analyzed to determine word usage data. Concepts that are associated with the words from the web page are also determined. The word usage data and concepts are used to recognize words of the user speech input. The method and system also include using the identified word usage data and concepts to create a summary of the web page. The summary is then voiced to the user.

Abstract: A computer-implemented method and system for generating speech models for use in speech recognition of a user speech input. Word conceptual networks are formed by grouping words with pre-selected pivot words. The groupings of words form phrases directed to pre-selected concepts. Phoneme networks are associated with the words in the word conceptual networks. The phoneme networks contain probabilities for recognizing the words in the word conceptual networks. A language model is partitioned into sub-language models based upon the pivot words. The sub-language models include the phoneme networks that are associated with the words grouped with the sub-language models' respective pivot words.

Abstract: A computer-implemented system and method for speech recognition of a user speech input. A language model is used to contain probabilities used to recognize speech, and an application domain description data store contains a mapping between pre-selected words and domains. A probability adjustment unit selects at least one domain based upon the user speech input. The probability adjustment unit adjusts the probabilities of the language model to recognize the user speech input based upon the words that are mapped to the selected domain.

Abstract: A computer-implemented method and system for processing requests voiced by a user. User speech input is received that contains words from the user that are directed to at least one concept. The user speech input contains a request for a service to be performed. Speech recognition of the user speech input generates recognized words. The concept of the user speech input is determined by applying fuzzy logic rules to the recognized words. The fuzzy logic rules define non-crisp relationships among predetermined concepts. The user's request is processed based upon the determined concept of the user speech input.

Abstract: A computer-implemented dynamic pronunciation system and method that includes a dictionary storage unit for containing word pronunciation rules. A dictionary generation unit determines a first set of possible pronunciation rules for a pre-selected word. A neural network accepts word spelling as an input and generates at least one pronunciation rule as an output. The pronunciation rule from the neural network is used within the first set of possible pronunciation rules for the pre-selected word to form a pronunciation dictionary.

Abstract: A computer-implemented system and method for processing speech input from a user. A call management unit receives a call from the user and through which the speech input is provided by the user. A speech management unit recognizes the user speech input through language recognition models. The language recognition models contains word recognition probability data derived from word usage on Internet web pages. A service management unit handles e-commerce requests contained in the user speech input. A web data management unit connected to an Internet network processes Internet web pages in order to generate the language recognition models for the speech management unit and to generate a summary of the Internet web pages. The generated summary is voiced to the user in order to service the user request.

Abstract: A computer-implemented system and method for speech recognition of a user speech input that contains a request to be processed. A speech recognition engine generates recognized words from the user speech input. A grammatical models data store contains word type data and grammatical structure data. The word type data contains usage data for pre-selected words based upon the pre-selected words' usage on Internet web pages, and the grammatical structure data contains syntactic models and probabilities of occurrence of the syntactic models with respect to exemplary user speech inputs. An understanding module applies the word type data and the syntactic models to the recognized words to select which of the syntactic models is most likely to match syntactical structure of the recognized words. The selected syntactic model is then used to process the request of the user speech input.

Abstract: A computer-implemented method and system for processing spoken requests from a user. A spoken first request from the user is received, and keywords in the first request are recognized for use as first searching criteria. The first request of the user is satisfied through use of the first searching criteria. A second spoken request from the user is received, and keywords in the second request are recognized for use as second searching criteria. Upon determining that additional data is needed to complete the second searching criteria before satisfying the second request, at least a portion of the recognized keywords of the first request is used to provide the additional data for completing the second searching criteria. Thereupon, the second request of the user is satisfied through use of the completed second searching criteria.

Abstract: A computer-implemented speech recognition method and system for handling noise contained in a user input speech. The user input speech from a user contains environmental noise, user vocalized noise, and useful sounds. A domain acoustic noise model is selected from a plurality of candidate domain acoustic noise models that substantially matches the acoustic profile of the environmental noise in the user input speech. Each of the candidate domain acoustic noise models contains a noise acoustic profile specific to a pre-selected domain. An environmental noise language model is adjusted based upon the selected domain acoustic noise model and is used to detect the environmental noise within the user input speech. A vocalized noise model is adjusted based upon the selected domain acoustic noise model and is used to detect the vocalized noise within the user input speech.

Abstract: A computer-implemented method and system for speech recognition of a user speech input. The user speech input which contains utterances from a user is received. A first language model recognizes at least a portion of the utterances from the user speech input. The first language model has utterance terms that form a general category. A second language model is selected based upon the identified utterances from use of the first language model. The second language model contains utterance terms that are a subset category of the general category of utterance terms in the first language model. Subset utterances are recognized with the selected second language model from the user speech input.

Abstract: A computer-implemented method and system for speech recognition of a user speech input. The user speech input contains a request that needs processing. A first noise probability model is applied to the user speech input at a first noise ratio level in order to recognize a first set of words in the user speech input. A second noise probability model is applied to the user speech input at a second noise ratio level in order to recognize a second set of words in the user speech input. The user's request is processed based upon which words are recognized in both the first set and second set of recognized words.

Abstract: A computer-implemented method and system for handling a speech dialogue with a user. Speech input from a user contains words directed to a plurality of concepts. The user speech input contains a request for a service to be performed. Speech recognition of the user speech input is used to generate recognized words. A dialogue template is applied to the recognized words. The dialogue template has nodes that are associated with predetermined concepts. The nodes include different request processing information. Conceptual regions are identified within the dialogue template based upon which nodes are associated with concepts that approximately match the concepts of the recognized words. The user's request is processed by using the request processing information of the nodes contained within the identified conceptual regions.

Abstract: A computer-implemented system and method for speech recognition of a user speech input. A plurality of language models contains words belonging to domains at different levels of specificity. A recognition unit recognizes words of the user speech input through use of the different language models. A dynamic language model generation unit generates a dynamic language model from the recognized words by examining both semantic and phonetic information of the recognized words. The dynamic language model is used to recognize the words in the user speech input.

Abstract: A computer-implemented method and system for speech recognition of a user speech input. A web page is retrieved from the Internet. Components of the web page and the components' type are identified in order to determine word usage data of the web page. The word usage data is used to recognize words of the user speech input.