Abstract: A non-transitory computer-readable recording medium stores an information searching program causing a computer to execute processing of: in an information search using a trained machine learning model generated by machine learning using training data in a first language, when a search condition is in the first language, translating the search condition to a second language different from the first language; re-translating the search condition translated to the second language to the first language; and performing the information search by inputting the search condition re-translated to the first language to the machine learning model; and when the search condition is in a language different from the first language, translating the search condition to the first language, and performing the information search by inputting the search condition translated to the first language to the machine learning model.

Abstract: An apparatus for processing an audio signal includes a separator for separating a first portion of a spectrum of the audio signal from a second portion of the spectrum of the audio signal, the first portion having a first signal characteristic and the second portion having a second signal characteristic. The apparatus includes a first bandwidth extender for extending a bandwidth of the first portion using first parameters associated with the first signal characteristic, for obtaining a first extended portion and includes a second bandwidth extender for extending a bandwidth of the second portion using second parameters associated with the second signal characteristic, for obtaining a second extended portion. The apparatus includes a combiner configured for using the first extended portion and the second extended portion for obtaining an extended combined audio signal.

Abstract: A system comprises a communications module; at least one processor coupled with the communications module; and a memory coupled to the at least one processor and storing processor-executable instructions which, when executed by the at least one processor, configure the at least one processor to provide, via the communications module, a first encryption key of an encryption key pair to a client device; receive, via the communications module and from a conversation agent server, a fulfillment request based on a natural language input transmitted from the client device to the conversation agent server; determine that the fulfillment request includes a request for personal data; obtain the requested personal data; encrypt the personal data with a second encryption key of the encryption key pair; and provide, via the communications module and to the conversation agent server, the encrypted personal data for transmission to the client device.

Abstract: An insight comprising a fact about a portion of data in a dataset is detected in the dataset. A context is determined by analyzing a natural language input, the context identifying an intent and an entity referenced by the natural language input. A relevance score is computed for the insight, the relevance score comprising a measure of similarity between a vector representation of the insight and a vector representation of the context, the vector representation of the insight comprising an encoding of the insight in multidimensional numerical form, the vector representation of the context comprising an encoding of the context in multidimensional numerical form. A selected insight is presented, the selected insight selected from a set of insights including the insight, the selected insight selected based on the relevance score.

Abstract: Disclosed herein are system, method, and computer program product embodiments for similarity scoring of sentences, while restricting distances between tokenized pairs in the sentences. An embodiment operates by determining a similarity of tokens between a first sequence of tokens and a second sequence of tokens to generate token pairs, determining a distance of relative positioning of token pairs in the first tokenized sequence and the second tokenized sequence and generating a score value that indicates the degree to which the first sentence matches the second sentence based on restricting matches to a maximum value of the distance of relative positions of the token pairs in the first tokenized sequence and the second tokenized sequence.

Abstract: Concealing a lost audio frame of a received audio signal is provided by performing a sinusoidal analysis of a part of a previously received or reconstructed audio signal, wherein the sinusoidal analysis involves identifying frequencies of sinusoidal components of the audio signal, applying a sinusoidal model on a segment of the previously received or reconstructed audio signal, wherein said segment is used as a prototype frame in order to create a substitution frame for a lost audio frame, and creating the substitution frame for the lost audio frame by time-evolving sinusoidal components of the prototype frame, up to the time instance of the lost audio frame, in response to the corresponding identified frequencies.

Abstract: The present disclosure relates to a difficult airway evaluation method and device based on a machine learning voice technology. The method includes the following steps: acquiring voice data of a patient; carrying out feature extraction on the voice data, obtaining a pitch period of pronunciations, and acquiring a voiced sound feature and unvoiced sound features based on the pitch period of pronunciations; and constructing a difficult airway evaluation classifier based on the machine learning voice technology, analyzing the received voiced sound feature and unvoiced sound features by the trained difficult airway evaluation classifier, and carrying out scoring on the severity of a difficult airway to obtain an evaluation result of the difficult airway.

Abstract: According to one embodiment, a difference extraction device includes processing circuitry. The processing circuitry acquires a text in which an input notation string is described. The processing circuitry converts the input notation string into a pronunciation string. The processing circuitry executes a pronunciation string conversion process in which the pronunciation string is converted into an output notation string. The processing circuitry extracts a difference by comparing the input notation string and the output notation string with each other.

Abstract: In an aspect, a computerized method for generating processed files of deposition testimony transcript designations may include accessing a file containing designations of contents of a textual transcript, quarantining errors in the designations, and generating a processed file containing processed designations of contents of the textual transcript having quarantined errors removed therefrom. In another aspect, a computerized method of generating designations for a deposition testimony transcript may include accessing designation information regarding designations made with respect to text of the deposition testimony transcript, accessing rules for generating designations based on the designation information, and generating the designations based on the rules.

Abstract: A method and apparatus for generating speech through neural text-to-speech (TTS) synthesis. A text input may be obtained (1310). Phoneme or character level text information may be generated based on the text input (1320). Context-sensitive text information may be generated based on the text input (1330). A text feature may be generated based on the phoneme or character level text information and the context-sensitive text information (1340). A speech waveform corresponding to the text input may be generated based at least on the text feature (1350).

Abstract: Examples described herein generally relate to a computer system including a knowledge graph storing a plurality of entities. A mining of a set of enterprise source documents within an enterprise intranet is performed, by an enterprise named entity recognition (ENER) model, to determine a plurality of entity names. An entity record is generated within a knowledge graph for a mined entity name from the linked entity names based on an entity schema and ones of the set of enterprise source documents associated with the mined entity name. The entity record includes attributes aggregated from the ones of the set of enterprise source documents associated with the mined entity name.

Abstract: A method and system are provided for processing natural language user queries for commanding a user interface to perform functions. Individual user queries are classified in accordance with the types of functions and a plurality of user queries may be related to define a particular command. To assist with classification, a query type for each user query is determined where the query type is one of a functional query requesting a particular new command to perform a particular type of function, an entity query relating to an entity associated with the particular new command having the particular type of function and a clarification query responding to a clarification question posed to clarify a prior user query having the particular type of function. Functional queries may be processed using a plurality of natural language processing techniques and scores from each technique combined to determine which type of function is commanded.

Abstract: Techniques performed by a data processing system for analyzing the lexical difficulty of words of textual content include analyzing a plurality of textual content sources to determine a first frequency at which each of a plurality of first words appears, analyzing search data to determine a second frequency at which each of the plurality of first words appear in searches for a definition, generating a lexical difficulty model based on the first frequency and the second frequency, the model is configured to receive a word as an input and to output a prediction for how difficult the word is likely to be for a user, receiving a request to analyze first textual content from a client device, analyzing the first textual content using the lexical difficulty model to generate lexical difficulty information, and sending a response to the client device that includes requested information.

Abstract: This application discloses a speech noise reduction method performed by a computing device. The method includes: obtaining a noisy speech signal, the noisy speech signal including a pure speech signal and a noise signal; estimating a posteriori signal-to-noise ratio and a priori signal-to-noise ratio of the noisy speech signal; determining a speech/noise likelihood ratio in a Bark domain based on the estimated posteriori signal-to-noise ratio and the estimated priori signal-to-noise ratio; estimating a priori speech existence probability based on the determined speech/noise likelihood ratio; determining a gain based on the estimated posteriori signal-to-noise ratio, the estimated priori signal-to-noise ratio, and the estimated priori speech existence probability, the gain being a frequency domain transfer function used for converting the noisy speech signal into an estimation of the pure speech signal; and exporting the estimation of the pure speech signal from the noisy speech signal based on the gain.

Abstract: A method includes identifying identigens for each word of a trusted phrase, where the identigens of a first word of the trusted phrase includes one or more different meanings of the first word. The method further includes identifying two adjacent words of the trusted phrase that are lacking an identigen pairing and determining whether the identigen pairing can be inferred for the two adjacent words based on known identigen pairings of other words of the trusted phrase. When the identigen pairing can be inferred for the two adjacent words, the method further includes adding to a knowledge database the identigen pairing of the two adjacent words.

Abstract: Computer implemented systems and methods of processing clinical documentation for a multi-axial coding scheme include inputting clinical documentation from memory operatively coupled with a computer system, and executing a natural language processor configured to process narrative text in the clinical documentation. The processor segments the narrative text based on boundaries defined in the clinical documentation, sequences words in the narrative text based on the segmentation, and maps the sequenced words to semantic objects in an ontology database. The ontology defines classes of semantic objects and relationships between them, corresponding to the multi-axial coding scheme. The semantic objects are converted into characters and output into slots in a medical code, with the characters positioned in the slots based on the multi-axial coding scheme.

Abstract: As an example, a server may receive, from a computing device, a submission created by an author. The submission includes book data associated with a book and author data associated with the author. The author data includes incarceration data indicating whether the author was incarcerated. The server may determine, based on the author data and the book data, that the submission is publishable. The server may create, based on the book data, a printable book, an e-book, and an audio book and make one or more of the printable book, the e-book, and the audio book available for acquisition.

Abstract: In general, techniques are described for various aspects of accessing datasets. A device comprising a memory configured to store the dataset, and a processor may be configured to perform the techniques. The processor may expose a language sub-surface specifying a natural language containment hierarchy defining a grammar for a natural language as a hierarchical arrangement of a plurality of language sub-surfaces. The processor may receive a query to access the dataset, the query conforming to a portion of the natural language provided by the exposed language sub-surface. The processor may transform the query into one or more statements that conform to a formal syntax associated with the dataset, access, based on the one or more statements, the dataset to obtain a query result, and output the query result.

Abstract: Systems, apparatuses, and methods are described for inverting neural embeddings. One or more forward neural embeddings associated with meanings, features, and/or characteristics of data samples may be generated for one or more data samples. One or more inverse neural embeddings associated with the one or more forward neural embeddings may be determined. One or more inverse feature sets for the one or more inverse neural embeddings may be generated.

Abstract: A mixed speech recognition method, a mixed speech recognition apparatus, and a computer-readable storage medium are provided. The mixed speech recognition method includes: monitoring an input of speech input and detecting an enrollment speech and a mixed speech; acquiring speech features of a target speaker based on the enrollment speech; and determining speech belonging to the target speaker in the mixed speech based on the speech features of the target speaker. The enrollment speech includes preset speech information, and the mixed speech is non-enrollment speech inputted after the enrollment speech.