Abstract: Systems and processes for providing differentiated advertising sponsorship of a fabricated reading product are provided. Natural language digital text characterized by a sentence, comprised of words is user selected. The text is linguistically analyzed in furtherance of displaying a fabricated reading product corresponding to the text. The words of the sentence of the text, and the sentences, are evaluated with regard to word/sentence attributes for the words of the sentences text in furtherance of supplying only the word/sentence attributes to an advertising sponsor. Based upon either or both of the word and sentence evaluation, determining whether to supply an ad from the advertising sponsor in relation to a display of the fabricated reading product, and, in connection to supplying an ad, further determining placement position of the ad in relation to the display of the fabricated reading product.

Abstract: A method executed by a computing device includes determining a set of identigens for each query word of a query to produce sets of identigens, where a set of identigens represents different meanings of a word of the query. The method further includes obtaining a first identigen selection for a first query word from the first set of identigens. The method further includes interpreting, using identigen pairing rules and based on the first identigen selection, the sets of identigens to produce a query entigen group. The method further includes accessing a knowledge database utilizing the query entigen group to produce a response entigen group. The method further includes generating a response to the query using the response entigen group, where the response includes at least one response word.

Abstract: Methods, apparatuses, and computer program products for multilingual simultaneous interpretation using a distributed ledger are disclosed. A multilingual interpretation server determines that a new word has been added to a first language node, the first language node corresponding to a first language, and broadcasts, to a plurality of other language nodes, a request to interpret the new word, wherein each of the plurality of other language nodes corresponds to a different language. Each of the plurality of language nodes interprets the new word into a particular language and adds the new word and one or more interpretations of the new word to an entry in a dictionary ledger. A multilingual interpretation service provides simultaneous multilingual translations of from a source language to a plurality of target languages using the shared distributed dictionary ledger. A multilingual interpretation client is provided for accessing services provided by the multilingual interpretation service.

Abstract: A method including detecting a webpage accessed by a user on a computing device via a browser. Content on the webpage is determined, and a model is applied to the content to determine a plurality of keyword sets. A network search is performed based on each of the plurality of keyword sets to generate a plurality of search results. The plurality of search results are compared to the content, and the plurality of search results are compared to each other. A factualness of the content is determined based on the comparing of the plurality of search results to the content and based on the comparing of the plurality of the search results to each other, and the user is notified via the browser of the factualness of the content.

Abstract: Systems and methods for natural language processing are described. Embodiments of the inventive concept are configured to receive an input sequence and a plurality of candidate long forms for a short form contained in the input sequence, encode the input sequence to produce an input sequence representation, encode each of the plurality of candidate long forms to produce a plurality of candidate long form representations, wherein each of the candidate long form representations is based on a plurality of sample expressions and each of the sample expressions includes a candidate long form and contextual information, compute a plurality of similarity scores based on the candidate long form representations and the input sequence representation, and select a long form for the short form based on the plurality of similarity scores.

Abstract: A method of providing sentiment analysis includes training a computer system to identify a polarity of a sentiment for a plurality of phrases and receiving, at the computer system, an input from a website. The input includes a text string including a phrase. The method includes determining, by the computer system, the polarity of the sentiment of the phrase by comparing the phrase to the plurality of phrases and sending, by the computer system, a command to the website that causes the website to display predetermined content based on the determined polarity of the sentiment of the phrase.

Abstract: In some examples, a computing device may implement a method that includes receiving microservice profile information at a microservice profiler, performing lexical analysis of the microservice profile information (where the lexical analysis produces tokenized information), generating microservice modification information by performing machine learning analysis of one or more inputs (where the one or more inputs comprise the tokenized information), and outputting the microservice modification information from the microservice profiler. The microservice profile information describes one or more characteristics of a microservice. The lexical analysis is performed by a lexical analysis engine of the microservice profiler, and the machine learning analysis is performed by a machine learning system of the microservice profiler.

Abstract: Described are systems, methods, apparatuses, and computer program product embodiments for automatically processing intent-based spoken language for SLU. The disclosed solution uses a scale-free network structured conversational knowledge graph that stores nodes representative of actions, objects, and intent names and edges representative of relationships between the nodes. For all phrases (including a sentence) from the same intent, the system calculates a mean feature vector using a Universal Sentence Embedding (USE) model as a feature element. The system also employs a multi-step intent detection strategy. A graph query technique may be used to match all potential intent nodes from the trained knowledge graph. The system may compute a covariance matrix between the feature element of an input phrase and feature elements of all potential intents. The major component of the covariance matrix along with the maximum covariance may be used to determine the final intent.

Abstract: Systems may perform analyses of claims included in a patent document. The systems may generate one or more search strings from the patent document and provide the one or more search strings to a third-party searching authority. The third-party searching authority may return a collection of documents responsive to the one or more search strings. In particular situations, the systems may re-rank the documents of the collection to provide a patent centric ranking. The systems may also analyze the documents of the collection with respect to the elements of the claims to generate various types of patent infringement and/or invalidity reports.

Abstract: A conference terminal and an embedding method of audio watermarks are provided. In the method, a first speech signal and a first audio watermark signal are received respectively. The first speech signal relates to a speaker corresponding to another conference terminal, and the first audio watermark signal corresponds to the another conference terminal. The first speech signal is assigned to a host path to output a second speech signal. The first audio watermark signal is assigned to an offload path to output a second audio watermark signal. The host path provides more digital signal processing (DSP) effects than the offload path. The second speech signal and the second audio watermark signal are synthesized to output a synthesized audio signal. The synthesized audio signal is adapted for audio playback. A completed audio watermark signal is outputted accordingly.

Abstract: A method manages bot dialogue. A user input is converted to a phrase vector. A set of identified tokens are identified by a token identification engine from the phrase vector. An unsupervised token is selected from the set of identified tokens. A supervised token is selected from the set of identified tokens. A voted token selected from the unsupervised token and the supervised token. A next token is identified based on a set of recent tokens that includes the voted token. The next token is presented as one of a voice communication and an email communication.

Abstract: A media edit point selection process can include a media editing software application programmatically converting speech to text and storing a timestamp-to-text map. The map correlates text corresponding to speech extracted from an audio track for the media clip to timestamps for the media clip. The timestamps correspond to words and some gaps in the speech from the audio track. The probability of identified gaps corresponding to a grammatical pause by the speaker is determined using the timestamp-to-text map and a semantic model. Potential edit points corresponding to grammatical pauses in the speech are stored for display or for additional use by the media editing software application. Text can optionally be displayed to a user during media editing.

Abstract: A method for extracting information from a document, comprising: receiving an identification of an entity to be extracted from the document; identifying candidates from the document, each candidate corresponding to a given element contained in the document and having a given location within the document; embedding the candidates, thereby obtaining an embedding vector for each candidate; for each candidate, comparing in a semantic space the respective embedding vector to previous embedding vectors associated with previous entity values previously chosen for the entity, thereby obtaining a first comparison result; for each candidate, comparing in a pixel space the given location within the document of the candidate to a location associated with the previous entity values previously chosen for the entity, thereby obtaining a second comparison result; sorting the candidates using the first and second comparison results obtained for each candidate, thereby obtaining sorted candidates; and outputting the sorted can

Abstract: An electronic audio file is received that comprises spontaneous speech responsive to a prompt in a non-native language of a speaker. Thereafter, the electronic audio file is parsed into a plurality of spoken words. The spoken words are then normalized to remove stop words and disfluencies. At least one trained content scoring model is then used to determine an absence of pre-defined key points associated with the prompt in the normalized spoken words. A list of the determined absent key points can be generated. This list can then be displayed/caused to be displayed in a graphical user interface along with feedback to improve content completeness. Related apparatus, systems, techniques and articles are also described.

Abstract: Systems and methods are described to receive a query from a user and provide a reply that is appropriate for an age group of the user. A query for a media asset is received, where such query comprises an inputted term, and the query is determined to be received from a user belonging to a first age group. A context of the inputted term within the query is identified, and in response to the determining, based on the identified context, that the inputted term of the query is inappropriate for the first age group, a replacement term for the inputted term that is related to the inputted term and is appropriate for the first age group in the context of the query is identified. The query is modified to replace the inputted term with the identified replacement term, and a reply to the modified query is generated for output.

Abstract: A processing method of a sound watermark and a speech communication system are provided. Multiple sinewave signals are generated. Frequencies of the sinewave signals are different from each other, and the sinewave signals belong to a high-frequency sound signal. A watermark pattern is mapped into a time-frequency diagram, to form a watermark sound signal. Two dimensions of the watermark pattern in a two-dimensional coordinate system respectively correspond to a time axis and a frequency axis in the time-frequency diagram. Each of multiple audio frames on the time axis corresponds to the sinewave signals with different frequencies on the frequency axis. A speech signal and the watermark sound signal are synthesized in a time domain to generate a watermark-embedded signal. Accordingly, a sound watermark may be embedded in real-time.

Abstract: Approaches presented herein enable delivery of real-time internet of things (IoT) feedback to optimize a public speaking performance. More specifically, a set of data representing a speaking performance of a user is captured and analyzed to generate a speaking performance profile of the user. This profile is compared to a reference speaking performance profile and, based on the comparison, a set of performance improvement strategies for the user is generated. A performance improvement strategy is selected from the set of performance improvement strategies based on an identification of an availability of a set of IoT devices for delivery of at least one of the strategies. Instructions are then communicated, responsive to the captured speaking performance associated with the user, to an available IoT device to deliver the selected performance improvement strategy to the user through an output user interface of the available IoT device during the speaking performance.

Abstract: A system configured to perform low power mode wakeword detection is provided. A device reduces power consumption without compromising functionality by placing a primary processor into a low power mode and using a secondary processor to monitor for sound detection. The secondary processor stores input audio data in a buffer component while performing sound detection on the input audio data. If the secondary processor detects a sound, the secondary processor sends an interrupt signal to the primary processor, causing the primary processor to enter an active mode. While in the active mode, the primary processor performs wakeword detection using the buffered audio data. To reduce a latency, the primary processor processes the buffered audio data at an accelerated rate. In some examples, the device may further reduce power consumption by including a second buffer component and only processing the input audio data after detecting a sound.

Abstract: A method and an apparatus for processing information are provided. The method can include: acquiring a word sequence obtained by performing word segmentation on two paragraphs in a text; inputting the word sequence into a to-be-trained natural language processing model to generate a word vector corresponding to a word in the word sequence; inputting the word vector into a preset processing layer of the to-be-trained natural language processing model; predicting whether the two paragraphs are adjacent, and a replaced word in the two paragraphs; and acquiring reference information of the two paragraphs, and training the to-be-trained natural language processing model to obtain a trained natural language processing model, based on the prediction result and the reference information.

Abstract: A system is provided comprising a processor and a memory storing instructions which configure the processor to process an original sentence structure through an encoder neural network to decompose the original sentence structure into an original semantics component and an original syntax component, process the original syntax component through a syntax variation autoencoder (VAE) to receive a syntax mean vector and a syntax covariance matrix, obtain a sampled syntax value from a syntax Gaussian posterior parameterized by the syntax mean vector and the syntax covariance matrix, process the original semantics component through a semantics VAE to receive a semantics mean vector and a semantics covariance matrix, obtain a sampled semantics vector from the Gaussian semantics posterior parameterized by the semantics mean vector and the semantics covariance matrix, and process the sampled syntax vector and the sampled semantics vector through a decoder neural network to compose a new sentence.