Abstract: According to one embodiment, a speech learning apparatus includes a detection unit, a first calculation unit, a generation unit, an addition unit and a speech synthesis unit. The first calculation unit calculates a score indicating a degree of emphasis of a keyword based on a type of the marker and a manner of selecting the keyword. The generation unit generates a synthesis parameter to determine a degree of reading of the keyword in accordance with the score and the type of the marker. The addition unit adds to the keyword a tag for reading the keyword in accordance with the synthesis parameter. The speech synthesis unit generates synthesized speech obtained by synthesizing speech of the keyword in accordance with the tag.

Abstract: According to one embodiment, a prosody editing apparatus includes a storage, a first selection unit, a search unit, a normalization unit, a mapping unit, a display, a second selection unit, a restoring unit and a replacing unit. The search unit searches the storage for one or more second prosodic patterns corresponding to attribute information that matches attribute information of the selected phrase. The mapping maps each of the normalized second prosodic patterns on a low-dimensional space. The restoring unit restores a restored prosodic pattern according to the selected coordinates. The replacing unit replaces prosody of synthetic speech generated based on the selected phrase by the restored prosodic pattern.

Abstract: According to one embodiment, a markup assistance apparatus includes an acquisition unit, a first calculation unit, a detection unit and a presentation unit. The acquisition unit acquires feature amount for respective tags, each of the tags being used to control text-to-speech processing of a markup text. The first calculation unit calculates, for respective character strings, a variance of feature amounts of the tags which are assigned to the character string in a markup text. The detection unit detects first character string assigned first tag having the variance not less than a first threshold value as a first candidate including the tag to be corrected. The presentation unit presents the first candidate.

Abstract: According to one embodiment, a document reading-out support apparatus is provided with first to third acquisition units, an extraction unit, a decision unit and a user verification unit. The first acquisition unit acquires a document having texts. The second acquisition unit acquires metadata having definitions each of which includes an applicable condition and a reading-out style. The extraction unit extracts features of the document. The third acquisition unit acquires execution environment information. The decision unit decides candidates of parameters of reading-out based on the features and the information. The user verification unit presents the candidates and accepts a verification instruction.

Abstract: According to one embodiment, an apparatus for supporting reading of a document includes a model storage unit, a document acquisition unit, a feature information extraction, and an utterance style estimation unit. The model storage unit is configured to store a model which has trained a correspondence relationship between first feature information and an utterance style. The first feature information is extracted from a plurality of sentences in a training document. The document acquisition unit is configured to acquire a document to be read. The feature information extraction unit is configured to extract second feature information from each sentence in the document to be read. The utterance style estimation unit is configured to compare the second feature information of a plurality of sentences in the document to be read with the model, and to estimate an utterance style of the each sentence of the document to be read.

Abstract: An adding metadata apparatus includes a first acquisition unit which acquires a first image, first metadata, and a first position within the first image, the first position being for displaying the first metadata; an extraction unit which extracts local features from the first image; a calculation unit which searches for a group of the local features within a predetermined distance from the first position, and calculates a representative point of the group; a search unit which matches the first image with a plurality of images stored in a database by using the local features, and searches for a second image which coincides with the local features; and a registration unit which calculates a second position, within the second image, corresponding to the representative point, and registers the second position and the first metadata as metadata for the second image.

Abstract: A content recommending server includes: a content information collecting section collecting content information including metadata of contents from a content server through a network; a content database storing the content information collected by the content information collecting section; a user profile collecting section collecting user profiles of users from user terminals through the network, each of the user profiles including each user's preference; a user profile database storing the user profiles, the user profiles including a subject user profile; a content indexer acquiring the metadata and generating content indices of the contents; a user indexer acquiring the user profiles from the user profile database and generating user indices of each of the users; an index database storing the content indices and the user indices; and a content recommending section receiving the subject user profile, searching the index database for an certain index corresponding to the subject user profile, and determining

Abstract: An apparatus includes: a module configured to extract category information and program abstracts of programs contained in an electronic program guide, extract program-specific terms from the program abstracts by morphological analysis and combine the category information and the program-specific terms to generate category-added terms; a module configured to analyze a history of programs viewed by a user based on the generated category-added terms to generate a preference vector indicating user's preferences for programs; a module analyzing the program abstracts based on the category-added terms to generate broadcast program vectors; a module generating a relevant term model for the category-added terms; a module calculating similarities between the preference vector and each of the broadcast program vectors based on the generated relevant term model; and a module outputting programs having the calculated similarities satisfying a predetermined condition as recommended programs matching with the user's prefere

Abstract: A viewing behavior learning apparatus includes: a viewing history acquiring unit that acquires a viewing record that indicates an attribute of a program and start and end times during which a viewer viewed the program; a viewing history dividing unit that divides the viewing record every discretized time points that is discretized by a unit time; a viewing history replicating unit that discretizes a viewing time period denoted by the divided viewing records by interval shorter than the unit time to obtain discretized viewing time periods; a viewing behavior storage unit that builds a model of the viewing behavior by use of a Bayesian network having the viewing time period and the attribute as random variables and stores a conditional probability table of the Bayesian network; and a viewing behavior updating unit that updates the conditional probability table using the discretized viewing time periods.

Abstract: There is provided with a program searching apparatus, including: an extracting unit extracting words or phrases described in plural program information as keywords; an identifying unit identifying categories to which the keywords belongs; a first calculating unit calculating a number of program information containing the keywords as first information; a second calculating unit calculating a number of keywords that belong to the categories as second information; a specifying unit specifying one program as a search query; a weight calculating unit calculating, for each of query keywords extracted from program information of the search query, a weight based on the first and second information; a similarity calculating unit calculating a similarity level to the search query with respect to a search target program according to the weight corresponding to a query keyword included in the program information of the search target program.

Abstract: A frequent pattern mining system includes: a candidate pattern generation unit for generating a candidate record set having one record or more as an element, generating a candidate item set by extracting the items that belong commonly to respective records, and calculating a length of the candidate item set; a pattern removing unit for removing the candidate record set corresponding to the candidate item set whose pattern length is below the minimum pattern length; a frequent pattern generation unit for extracting all subsets whose pattern length is more than the minimum pattern length from the candidate item set; and the candidate record set generation unit that generates repeatedly an union of sets of two candidate record sets, in which only one element is different mutually, from the candidate record set, a number of records of which is largest, as a new candidate record set until the new candidate record set is not generated.

Abstract: A program information providing system includes: a genre selecting unit that selects a selected program genre from among a plurality of program genres contained in program information based on a selection criterion obtained from frequency information that indicates frequencies of each of the program genres during a predetermined time period; a preference model generating unit that generates a preference model describing a causal relationship between a cause leading to a viewing and a viewed result, based on the selected program genre and viewing history information of the viewer; and a recommended program list generating unit that generates a recommended program list by using the preference model generated by the preference model generating unit.

Abstract: A time series data prediction/diagnosis apparatus includes a first creator creating a model series using time series data items sequentially input, a first calculator calculating a prediction error for the model series at each input of a new time series data item, a second creator creating a plurality of model series candidates when an error between the new time series data item and the model series is larger than a predetermined error, a selector selecting an optimal model series among the plurality of model series candidates and set the optimal model series to a new model series, a second calculator calculating a prediction value using the new model series, and a diagnosis unit diagnosing why the prediction value is led for an output value by the second calculator and add a diagnosis result to the prediction value.

Abstract: A membrane switch comprises a pair of flexible sheets connected together with the respective inner surfaces thereof provided with contacts and terminals respectively connected to the contacts facing each other and spaced apart by a spacer, and an output flat cable held between the pair of flexible sheets with the leader lines thereof in electrical contact respectively with the terminals. One of the contacts is formed on the inner surface of one of the pair of flexible sheets by evaporation and etching. The rest of the contacts are formed on the inner surface of the other flexible sheet by evaporation and etching. A connecting film is formed over the periphery of the inner surface of at least one of the pair of flexible sheets.