International Business Machines Corporation

Globalfoundries Inc.

Arm Limited

Karthik Sankaranarayanan

Jaydeep Sen

Diptikalyan Saha

Ashish Mittal

Abhijit Mishra

Parag Jain

Amar Prakash Azad

Samarth Bharadwaj

Karthik Visweswariah

Saneem Ahmed Chemmengath

Anirban Laha

Suranjana Samanta

Manasa Jammi

Shreya Khare

Sameep Mehta

Vibha Singhal Sinha

Vinayaka D Pandit

Alberto Giammaria

Pratyush Kumar

Shantanu Ravindra Godbole

Manish Kesarwani

Rajasekar Krishnamurthy

Sumit Bhatia

Sreyash Kenkre

Mikael Yves Marie Rien

Karthikeyan Ponnalagu

Deepak Vijaykeerthy

Saravanan Krishnan

Ayushi Dalmia

Praduemn K Goyal

Roma Rudra

Shashank Guruprasad

Senthil K K Mani

A method, system, and computer program product for automated artificial intelligence (AI) factsheet generation for modeling and model customization in speech to text (STT) services. The method receives audio data for a user. The audio data contains human speech. Text data is generated, using a first speech to text model, to represent the human speech of the audio data. A set of transcription errors of the first speech to text model are identified. A set of AI factsheets are generated to describe model metadata for the first speech to text model. Based on the set of transcription errors and the set of AI factsheets, the method generates a second speech to text model customized to the user.

Artificial intelligence factsheet generation for speech recognition

A natural language processing approach for generating domain specific reasoning-based meaning representations. The approach may include receiving a user query via structured or unstructured data. The approach may also include generating a structured query from the user query using domain specific ontology and universal facts. Further, the approach many include the structured query may be analyzed to determine if the structured query has been assigned consistent concepts, properties and actions. Additionally, the approach may involve correcting the structured query if it is determined the structured query is inconsistent with the domain ontology and the universal facts.

Reasoning based natural language interpretation

According to one implementation of the present disclosure, a circuit includes: two or more metal wires, respective XOR gates coupled to each of the two or more top metal wires, a shift register having outputs coupled to the XOR gates, an OR gate configured to receive each of the outputs of the XOR gates, and a latch configured to receive an output of the OR gate and transmit an output signal corresponding to an alarm signal.

Alarm systems and circuits

Methods, systems, and computer program products for automated domain-specific constrained decoding from speech inputs to structured resources are provided herein. A computer-implemented method includes converting at least a portion of at least one user-provided speech utterance into text by processing the at least one user-provided speech utterance using an artificial intelligence-based automatic speech recognition model; automatically training an artificial intelligence-based decoding engine, wherein automatically training the artificial intelligence-based decoding engine comprising constraining the artificial intelligence-based decoding engine based at least in part on a domain-specific model and the artificial intelligence-based automatic speech recognition model; and generating at least one of one or more domain-specific text outputs related to one or more structured resources associated with the domain and one or more domain-specific action outputs related to the one or more structured resources associated with the domain by processing at least a portion of the text using the artificial intelligence-based decoding engine.

Automated domain-specific constrained decoding from speech inputs to structured resources

Methods, systems, and computer program products for active learning for natural language question answering are provided herein. A computer-implemented method includes generating a semantic signature of a natural language query; generating a SQL signature for a SQL query corresponding to the natural language query; determining whether a set of mappings includes a semantic signature matching the generated semantic signature, wherein each mapping in the set is between (i) a given semantic signature and (ii) a SQL signature representing a class of SQL queries corresponding to the given semantic signature; and in response to determining that the set of mappings does not include the generated semantic signature, adding a mapping between the generated semantic signature and the generated SQL signature to the set of mappings.

Active learning for natural language question answering

Methods, systems and computer program products for multi-style text transformation are provided herein. A computer-implemented method includes selecting at least one set of style specifications for transforming at least a portion of input text. The at least one set of style specifications include one or more target writing style domains selected from a plurality of writing style domains, weights for each of the target writing style domains representing relative impact of the target writing style domains for transformation of at least a portion of the input text, and weights for each of a set of linguistic aspects for transformation of at least a portion of the input text. The computer-implemented method also includes generating one or more style-transformed output texts based at least in part on the at least one set of style specifications utilizing at least one unsupervised neural network.

Controllable style-based text transformation

Methods, systems, and computer program products for processing natural language analytics queries are provided herein. A computer-implemented method includes obtaining a natural language query comprising an analytics function; applying domain reasoning using a predefined grammar for a plurality of different predefined categories of analytics functions to assign the analytics function of the natural language query into a given analytics function category; identifying predefined arguments and a predefined sequence of actions associated with the given analytics function category; instantiating the analytics function using the predefined arguments and the predefined sequence of actions; interpreting the instantiated analytics function in the context of a domain ontology to generate a target executable query to implement the instantiated analytics function; and executing the predefined sequence of actions for the given analytics function class on a result of the target executable query to obtain an answer to the natural language query.

Natural language analytics queries

Methods, systems, and computer program products for unsupervised tunable stylized text transformations are provided herein. A computer-implemented method includes identifying amendable portions of input text by processing at least a portion of the input text using at least one neural network; determining stylistic text modifications to the amendable portions of the input text, the text modifications encompassing a set of stylistic parameters, wherein said determining comprises processing at least a portion of the set of stylistic parameters using at least one neural network; generating a stylized output set of text by transforming at least a portion of the input text, wherein said transforming comprises modifying at least one of the amendable portions of the input text via at least one of the stylistic text modifications encompassed by the set of stylistic parameters; and outputting the stylized output set of text to at least one user.

Unsupervised tunable stylized text transformations

One embodiment provides a method, including: receiving a query from a user; identifying that a desired definition of the at least one term is unknown, by determining that the at least one term does not map to a term having a known definition; receiving the definition of the at least one term from the user; adding the definition to a domain grammar comprising (i) domain-specific terminology and (ii) definitions corresponding to the terms within the domain grammar, wherein the adding comprises (a) extracting expressions from the requested definition and (b) adding, for the at least one term, the expressions into a structured format within the domain grammar; combining (iii) the requested definition and (iv) terms from the parsed query having previously known definitions into a complete query; and providing a response to the query by executing the complete query on a knowledge store.

Domain query execution using user-provided definition

Methods, systems, and computer program products for generating concept images of human poses using machine learning models are provided herein. A computer-implemented method includes identifying events from input data by applying a machine learning recognition model to at least a portion of the input data, wherein the identifying comprises (i) detecting multiple entities from the input data and (ii) determining behavioral relationships among at least a portion of the multiple entities; generating, using a machine learning interpretability model and at least a portion of the identified events, images illustrating human poses related to at least a portion of the identified events; outputting at least a portion of the generated images to a user; and updating the machine learning recognition model based at least in part on (i) at least a portion of the generated images and (ii) input from the user.

Generating concept images of human poses using machine learning models

Embodiments are disclosed for correcting a natural language interface database (NLIDB) system. The techniques include receiving feedback indicating that an answer provided in response to a question for an NLIDB system is inaccurate. The techniques further include finding an ontology element for a datastore of the NLIDB system that matches to the feedback. The techniques also include selecting candidate annotations for the NLIDB system based on the ontology element and a data type of the ontology element. Additionally, the techniques include generating a question-answer (QA) pair for each of the candidate annotations. Further, the techniques include adding one of the candidate annotations to annotations for a natural language query (NLQ) engine of the NLIDB system based on a client verification of the QA pair.

Natural language interface databases

Text suggestions are generated. A document is received, and a portion score for at least one portion of the document is generated. A global assessment score for at least two portions of the document is also generated. A variation between the portion score and the global assessment score is calculated. It is determined that the variation is above a threshold variation, and at least one text change suggestion is generated.

Real-time assessment of text consistency

One embodiment provides a method, including: receiving, from a user, input for generating an article, wherein the input comprises (i) an indication of topic-specific requirements for the article that are dependent upon a topic of the article and (ii) an indication of non-topic-specific requirements for the article that are independent of the topic of the article; creating at least one query from the input; retrieving, from secondary sources by performing a search utilizing the query, structured information contextually relevant to the topic; and from the structured information, generating the article, wherein the article comprises a coherent and grammatically fluid structured article generated in view of the topic-specific requirements and the non-topic-specific requirements.

Structured article generation

A method, computer system, and computer program product for a conversational system driven by a semantic network with a library of templated query operators are provided. The embodiment may include loading one or more operators for the conversational system to the library of templated query operators. The embodiment may also include receiving a query statement from a user. The embodiment may further include identifying an operator from the library to process the received query. The embodiment may also include identifying one or more input terms for the identified operator within the received query. The embodiment may further include generating one or more output terms based on processing the one or more identified input terms using the identified operator. The embodiment may also include generating a natural language response to the received query based on the one or more generated output terms.

Designing conversational systems driven by a semantic network with a library of templated query operators

Systems and methods are provided for generating nested queries from natural language queries. In particular, system and methods are provided to implement natural language interfaces to databases (NLIDB) frameworks which are configured to apply intelligent reasoning over domain semantics to detect and generate nested queries across different domains without the need for domain specific training or utilizing domain-specific semantic templates for mapping a natural language query to a structured query.

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Bengaluru, India

Karthik Sankaranarayanan