Abstract: An audio signal decoding apparatus is provided that includes a receiver that receives an encoded information, a memory, and a processor that demultiplexes the encoded information, including encoding parameters that are used for decoding a low frequency spectrum and index information that identifies a most correlated portion from a low frequency spectrum for one or more high frequency subbands. The processor also replicates a high frequency subband spectrum based on the index information using a synthesized low frequency spectrum, the synthesized low frequency spectrum being obtained by decoding the encoding parameters. The processor further estimates a frequency of a harmonic component in the synthesized low frequency spectrum, adjusts a frequency of a harmonic component in the high frequency subband spectrum using the estimated harmonic frequency, and generates an output signal using the synthesized low frequency spectrum and the high frequency subband spectrum.

Abstract: System and methods for creating structured or semi-structured representations of information extracted from unstructured text data sources are described. In some embodiments, without requiring a predefined target data structure, the methods identify the grammatical and semantic attributes and context information in a text content, and create object-properties association data as knowledge and information extracted from the unstructured data, and represent such information in a structured or semi-structured format to facilitate search and trend analysis. In some other embodiments, the methods identify the types of information contained in the unstructured data, and for a pre-defined target information type, the methods identify the context and content of the portion of the text that represents the target information type, and extract the text, attach a tag or label to the extracted text, and store or display the data in a database table format or xml format for further pattern and trend analysis.

Abstract: Disclosed is an improved system for performing intelligent text reduction on text strings for optimal display in a variety of user interface display elements. The system includes a smart text reduction algorithm that can shorten text strings as necessary in response to resizing the user interface or elements therein. The system also includes a design time user interface for application developers (or other users) to design graphical user interfaces in a collaborative workspace. The design time user interface incorporates the smart text reduction algorithm to enable designers to modify user interface display elements and run the text reduction algorithm on any text strings that no longer fit within the modified display elements. The described embodiments can also translate text strings of user interface display elements and can execute the smart text shortening algorithm on the translated text strings accordingly.

Abstract: An autocorrelation calculating part calculates autocorrelation Ro(i) from an input signal. A predictive coefficient calculating part performs linear predictive analysis using modified autocorrelation R?o(i) obtained by multiplying the autocorrelation Ro(i) by a coefficient wo(i). Here, it is assumed that a case where, for at least part of each order i, the coefficient wo(i) corresponding to each order i monotonically increases as a value having negative correlation with a fundamental frequency of an input signal in a current frame or a past frame increases and a case where the coefficient wo(i) monotonically decreases as a value having positive correlation with a pitch gain in a current frame or a past frame increases, are included.

Abstract: A method and an apparatus for decoding a speech/audio bitstream are disclosed, where the method for decoding a speech/audio bitstream includes determining whether a current frame is a normal decoding frame or a redundancy decoding frame, obtaining a decoded parameter of the current frame by means of parsing when the current frame is a normal decoding frame or a redundancy decoding frame, performing post-processing on the decoded parameter of the current frame to obtain a post-processed decoded parameter of the current frame, and using the post-processed decoded parameter of the current frame to reconstruct a speech/audio signal.

Abstract: An autocorrelation calculating part calculates autocorrelation Ro(i) from an input signal. A predictive coefficient calculating part performs linear predictive analysis using modified autocorrelation R?o(i) obtained by multiplying the autocorrelation Ro(i) by a coefficient wo(i). Here, it is assumed that a case where, for at least part of each order i, the coefficient wo(i) corresponding to each order i monotonically increases as a value having negative correlation with a fundamental frequency of an input signal in a current frame or a past frame increases and a case where the coefficient wo(i) monotonically decreases as a value having positive correlation with a pitch gain in a current frame or a past frame increases, are included.

Abstract: A bit allocating method is provided that includes determining the allocated number of bits in decimal point units based on each frequency band so that a Signal-to-Noise Ratio (SNR) of a spectrum existing in a predetermined frequency band is maximized within a range of the allowable number of bits for a given frame; and adjusting the allocated number of bits based on each frequency band.

Abstract: A vector joint encoding/decoding method and a vector joint encoder/decoder are provided, more than two vectors are jointly encoded, and an encoding index of at least one vector is split and then combined between different vectors, so that encoding idle spaces of different vectors can be recombined, thereby facilitating saving of encoding bits, and because an encoding index of a vector is split and then shorter split indexes are recombined, thereby facilitating reduction of requirements for the bit width of operating parts in encoding/decoding calculation.

Abstract: An embodiment provides methods and arrangements for visualizing and exploring natural-language text. In an embodiment, natural language text is received, and this is parsed to form a directed graph comprising a plurality of nodes. The directed graph is converted to an outline graph comprising core nodes and layer nodes. The outline graph is simplified, and there is created, for display on a user interface, an interactive visual representation of the simplified outline graph. Other variants and embodiments are broadly contemplated herein.

Abstract: A first encoding unit generates a first encoded signal by encoding a component within a first band in a voice signal. A frequency shifting unit shifts the frequency of a component within a second band in the voice signal, the second band having a frequency higher than that of the first band, to the frequency of a component within the first band. A second encoding unit generates a second encoded signal by encoding the component whose frequency has been shifted in the frequency shifting unit. An output unit outputs both the first encoded signal generated in the first encoding unit and the second encoded signal generated in the second encoding unit.

Abstract: In accordance with an aspect, there is provided a system and method for electronic communications that involves machine learning and natural language processing for contact relationship discovery, ranking and retrieval. In accordance with an aspect, there is provided a system and device that discovers contacts related to user search terms, quantitatively measures and ranks the strength between contact relationships according to a score calculated by natural language processing and machine learning. The system generates visual effects to present recommendations to the user with multiple alternate route options to establish relationships between contacts.

Abstract: A system of multi-modal transmission of packetized data in a voice activated data packet based computer network environment is provided. A natural language processor component can parse an input audio signal to identify a request and a trigger keyword. Based on the input audio signal, a direct action application programming interface can generate a first action data structure, and a content selector component can select a content item. An interface management component can identify first and second candidate interfaces, and respective resource utilization values. The interface management component can select, based on the resource utilization values, the first candidate interface to present the content item. The interface management component can provide the first action data structure to the client computing device for rendering as audio output, and can transmit the content item converted for a first modality to deliver the content item for rendering from the selected interface.

Abstract: Disclosed is the technology for dynamic and intelligent generation of dialog recommendations for the users of chat information systems based on multiple criteria. An example method may include receiving a speech-based user input, recognizing at least a part of the speech-based user input to generate a recognized input, and providing at least one response to the recognized input. The method may further include identifying at least one triggering event, generating at least one dialog recommendation based at least in part on the identification, and presenting the at least one dialog recommendation to a user via a user device.

Abstract: A content generation service is described that generates content for electronic documents in different languages based upon templates. The templates may include paragraph templates composed of sentence types including sentence templates. The sentence templates may further include variables having corresponding attributes. Each of the paragraph templates, sentence templates, and attributes may be hierarchically organized. The content generation service may obtain data describing an item of interest, such as a travel item. The obtained data may further specify a document language, section and paragraph for which content is to be generated. Content is generated for variables in hierarchical order, with higher ranked paragraphs considered first. Within the highest ranked paragraph, a sentence type is selected and the variables within the highest ranked sentence template of the sentence type are considered.

Abstract: Systems and methods of voice activated thread management in a voice activated data packet based environment are provided. A natural language processor (“NLP”) component can receive and parse data packets comprising a first input audio signal to identify a first request and a first trigger keyword. A direct action application programming interface (“API”) can generate a first action data structure with a parameter defining a first action. The NLP component can receive and parse a second input audio signal to identify a second request and a second trigger keyword, and can generate a second action data structure with a parameter defining a second action. A pooling component can generate the first and second action data structures into a pooled data structure, and can transmit the pooled data structure to a service provider computing device to cause it device to perform an operation defined by the pooled data structure.

Abstract: A mechanism is provided in a data processing system configured with a natural language processing pipeline executing on at least one processor of the data processing system, for class narrowing for answer lookups. The natural language processing pipeline annotates an input question with a verb in the input question and a syntactic relation between the verb and a focus of the question. A class narrowing component of the natural language processing pipeline finds an entry in a verb/type lookup resource corresponding to the verb and the syntactic relation. The entry comprises the verb, the syntactic relation, and a set of classes. Each given class in the set of classes has a corresponding frequency value representing a frequency the given class occurs with the syntactic relation to the verb. The class narrowing component performs class-narrowed type-restricted answer lookup from a topology based on the entry in the verb/type lookup resource to generate a set of candidate answers.

Abstract: Snippets can be represented in a language-independent semantic manner. Each portion of a snippet can be represented by a combination of a semantic representation and a syntactic representation, each in its own dimensional space. A snippet can be divided into portions by constructing a dependency structure based on relationships between words and phrases. Leaf nodes of the dependency structure can be assigned: A) a semantic representation according to pre-defined word mappings and B) a syntactic representation according to the grammatical use of the word. A trained semantic model can assign to each non-leaf node of the dependency structure a semantic representation based on a combination of the semantic and syntactic representations of the corresponding lower-level nodes. A trained syntactic model can assign to each non-leaf node a syntactic representation based on a combination of the syntactic representations of the corresponding lower-level nodes and the semantic representation of that node.

Abstract: Interactive content containing audio or video may be provided in conjunction with non-interactive content containing audio or video to enhance user engagement and interest with the contents and to increase the effectiveness of the distributed information. Interactive content may be directly inserted into the existing, non-interactive content. Additionally or alternatively, interactive content may be streamed in parallel to the existing content, with only minimal modification to the existing content. For example, the server may monitor content from a content provider; detect an event (e.g., detecting a marker embedded in the content stream, or in a data source external to the content stream); upon detection of the event, play interactive content at one or more designated times while silencing the content stream of the content provider (e.g., by muting, pausing, playing silence.) The marker may be a sub-audible tone or metadata associated with the content stream.

Abstract: User interactions with a computing system are sensed and recorded. The recording represents a process for controlling a computer system. Voice input are received and the computer system actions that are taken based upon the voice inputs and a task recording.

Abstract: Systems, methods, and apparatuses are presented for a novel natural language tokenizer and tagger. In some embodiments, a method for tokenizing text for natural language processing comprises: generating from a pool of documents, a set of statistical models comprising one or more entries each indicating a likelihood of appearance of a character/letter sequence in the pool of documents; receiving a set of rules comprising rules that identify character/letter sequences as valid tokens; transforming one or more entries in the statistical models into new rules that are added to the set of rules when the entries indicate a high likelihood; receiving a document to be processed; dividing the document to be processed into tokens based on the set of statistical models and the set of rules, wherein the statistical models are applied where the rules fail to unambiguously tokenize the document; and outputting the divided tokens for natural language processing.