Abstract: In one embodiment, a computer-implemented method includes receiving, through a user interface (UI) of an artificial-reality (AR) design tool, a selection of a configurable interface element to place the AR design tool and the UI into a configure phase to configure an AR effect. The computer-implemented method further includes receiving, through the UI of the AR design tool after the AR design tool and the UI are placed into the configure phase in response to selecting the configurable interface element, instructions to add a voice-command module to the AR effect. The computer-implemented method further includes configuring, while the AR design tool and the UI are placed into the configure phase, one or more parameters of the voice-command module. The computer-implemented method further includes generating the AR effect utilizing a particular voice command at runtime based on configured one or more parameters of the voice-command module.

Abstract: A portable communication device is provided for voice recognition and comprises a display, communication circuitry, a microphone, at least one processor including a first processor and a second processor, and a memory storing instructions, when executed by the at least one processor, cause the portable communication device to: receive a first voice input via the microphone while a specified application is running; determine whether a voice recognition is to be performed with respect to the specified application by one of the first processor and the second processor; in case that the voice recognition is to be performed with respect to the specified application by the first processor; when the first voice input includes a wakeup command which is different from a designated command for the specified application by the voice recognition of the first processor, transmit a second voice input received after the first voice input through the communication circuitry to an external electronic device, and when the firs

Abstract: Various embodiments contemplate systems and methods for performing automatic speech recognition (ASR) and natural language understanding (NLU) that enable high accuracy recognition and understanding of freely spoken utterances which may contain proper names and similar entities. The proper name entities may contain or be comprised wholly of words that are not present in the vocabularies of these systems as normally constituted. Recognition of the other words in the utterances in question, e.g. words that are not part of the proper name entities, may occur at regular, high recognition accuracy. Various embodiments provide as output not only accurately transcribed running text of the complete utterance, but also a symbolic representation of the meaning of the input, including appropriate symbolic representations of proper name entities, adequate to allow a computer system to respond appropriately to the spoken request without further analysis of the user's input.

Abstract: The present disclosure discloses a speech recognition method and apparatus, and relates to the field of speech and deep learning technologies. A specific implementation scheme involves: acquiring candidate recognition results with first N recognition scores outputted by a speech recognition model for to-be-recognized speech, N being a positive integer greater than 1; scoring the N candidate recognition results based on pronunciation similarities between candidate recognition results and pre-collected popular entities, to obtain similarity scores of the candidate recognition results; and integrating the recognition scores and the similarity scores of the candidate recognition results to determine a recognition result corresponding to the to-be-recognized speech from the N candidate recognition results. The present disclosure can improve recognition accuracy.

Abstract: The present disclosure provides a language model based writing aid method, apparatus and system. The method includes: a server acquiring original text, where the original text may be writing text already generated and/or user input text; the server inputting the original text into a language model to generate a preset number of pieces of writing text, where the writing text and the original text have a correlation; the server sending the preset number of pieces of writing text to a frontend interface. The method of the present disclosure enables a computer to aide a user in text creating so that intelligence for writing aid is improved.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a sequence generation neural network. One of the methods includes obtaining a batch of training examples; for each of the training examples: processing the training network input in the training example using the neural network to generate an output sequence; for each particular output position in the output sequence: identifying a prefix that includes the system outputs at positions before the particular output position in the output sequence, for each possible system output in the vocabulary, determining a highest quality score that can be assigned to any candidate output sequence that includes the prefix followed by the possible system output, and determining an update to the current values of the network parameters that increases a likelihood that the neural network generates a system output at the position that has a high quality score.

Abstract: Aspects of the present disclosure provide systems and methods for access control using multi-factor validation. In an example, an access control system is designed to be used in conjunction with a first recognition system, such as facial recognition system, a gait recognition system, or audio recognition system, that uses a confidence level to determine whether individuals are authorized to access a restricted area. When the first recognition system is unable to confidently identify the individual, a second recognition system, such as a mobile device system or access card system, may be used to provide second factor verification. Further, stored recognition data may be updated to include information gathered by the first recognition system in response to use of the second factor verification.

Abstract: Embodiments described herein include a method for insertion of formatted text with speech recognition. One embodiment of the method includes creating a speech recognition command and executing the speech recognition command. Creating the speech recognition command may include receiving a selection by a user to add a plurality of actions to the speech recognition command and receiving a user-defined trigger command for the speech recognition command. In some embodiments, creating the speech recognition command includes receiving a definition of the text grammar, wherein the definition of the text grammar includes at least one command part and at least one command definition and storing the speech recognition command.

Abstract: The present invention provides a method and system for analyzing human speech during natural language processing interactions between humans and computers to aid in computer learning. The method processes human language tutorial videos each having a visual track, an audio track and captions. Multiple videos are simultaneously processed in parallel using stream processing to identify spoken words or phrases in the videos by comparing them with benchmark words/phrases stored on a computer. Confidence scores are determined for each of the spoken words/phrases which are assigned to a list of the benchmark words/phrases on the computer when a threshold value is met. A system administrator can identify spoken words/phrases to which the threshold value is not met.

Abstract: A method (and system) of determining confusable list items and resolving this confusion in a spoken dialog system includes receiving user input, processing the user input and determining if a list of items needs to be played back to the user, retrieving the list to be played back to the user, identifying acoustic confusions between items on the list, changing the items on the list as necessary to remove the acoustic confusions, and playing unambiguous list items back to the user.

Abstract: Sequential speech recognition using two unequal automatic speech recognition (ASR) systems may be provided. The system may provide two sets of vocabulary data. A determination may be made as to whether entries in one set of vocabulary data are likely to be confused with entries in the other set of vocabulary data. If confusion is likely, a decoy entry from one set of the vocabulary data may be placed in the other set of vocabulary data to ensure more efficient and accurate speech recognition processing may take place.

Abstract: The invention relates to a method and a device for the natural-language recognition of a vocal expression. A vocal expression of a person is detected and converted into a voice signal to be processed by a voice recognition device. Afterwards, the voice signal is analyzed at the same time or sequentially in a plurality of voice recognition branches of the voice recognition device using a plurality of grammars, wherein the recognition process is successfully completed if the analysis of the voice signal in at least one voice recognition branch supplies a positive recognition result.

Abstract: A visualization development system is provided. The system includes a visualization tool to develop one or more visualizations and a grammar engine that operates with the visualization tool to automatically detect visualization problems during the development of the visualizations.