Abstract: An electronic device and a control method thereof are provided. The electronic apparatus includes a voice input unit, a display, a memory storing at least one instruction, and a processor configured to execute the at least one instruction. The processor is configured to: based on a voice of a user being input through the voice input unit, recognize the user who has uttered the voice by comparing the voice with a plurality of pre-registered voices; and control the display to display an indicator corresponding to the recognized user.

Abstract: To be able to convert to a voice of the desired attribution. A learning unit learns a converter to minimize a value of a learning criterion of the converter, learns a voice identifier to minimize a value of a learning criterion of the voice identifier, and learns an attribution identifier to minimize a value of a learning criterion of the attribution identifier.

Abstract: The disclosure relates to an artificial intelligence (AI) system that simulates functions such as cognition and judgment of the human brain by utilizing machine learning algorithms such as deep learning and its applications. A method in which a device provides translation information of an application includes obtaining a resource file of an application through an operating system (OS) of the device; translating text to be displayed on an execution screen of the application from the obtained resource file by using an artificial intelligence model; generating the execution screen of the application by using the resource file and the translated text; and displaying the generated execution screen, wherein the translating includes translating the text of a first language into a second language by applying at least a part of data in the resource file to the artificial intelligence model trained to translate the text to be displayed on the execution screen of the application.

Abstract: Providing speech-to-text (STT) transcription by a user endpoint device includes initiating an audio communication between an enterprise server and the user endpoint device, the audio communication comprising a voice interaction between a user associated with the user endpoint device and an agent associated with an agent device to which the enterprise server routes the audio communication; performing a first STT of at least a portion of the voice interaction to produce a first transcribed speech in a first language; concurrent with performing the first STT, performing, by the user endpoint device, a second STT of the at least the portion of the voice interaction to produce a second transcribed speech in a second language different than the first language, and transmitting the at least the portion of the voice interaction and at least the first transcribed speech from the user endpoint device to the enterprise server.

Abstract: Devices and methods to track contact between persons using acoustic voiceprint identification from stored audio signals are presented herein.

Abstract: Systems and methods to implement commands based on selection sequences to a user interface are disclosed. Exemplary implementations may: store, electronic storage, a library of terms utterable by users that facilitate implementation of intended results; obtain audio information representing sounds captured by a client computing platform; detect the spoken terms uttered by the user present within the audio information; determine whether the spoken terms detected are included in the library of terms; responsive to determination that the spoken terms are not included in the library of terms, effectuate presentation of an error message via the user interface; record a selection sequence that the user performs subsequent to the presentation of the error message that causes a result; correlate the selection sequence with the spoken terms based on the selection sequence recorded subsequent to error message to generate correlation; and store the correlation to the electronic storage.

Abstract: A method and system to automatically convert a presentation with slide materials to a digitized notetaking resource, by inputting a media stream from a presentation to a compute server, converting the media stream by segmenting the video into smaller segments, transcribing audio of the presenter's speech into text. Time stamp metadata is associated to elements of the segmented video (and, if available, slide data), audio, and transcribed text, and the elements are time ordered. A user interface is provided displaying elements of the segmented video/slide data and transcribed text. The user interface enables playback of the elements of the segmented video/slide data, audio of the presenter's speech, and transcribed text, wherein playback items are time-matched. Different times can be selected by a user, wherein the selected elements are made prominent in the display, with the audio of the presenter's speech also being time-matched to the selection.

Abstract: A sound data processing method includes acquiring sound data of a target by input. The sound data processing method further includes: generating similar sound data that becomes a similar sound similar to the sound data of the target, based on the sound data of the target; and performing machine learning by using the acquired sound data of the target and the generated similar sound data as learning sound data, and generating a learning model for performing classification determination related to the sound data of the target.

Abstract: Implementations relate to an automated assistant that can respond to communications received via a third party application and/or other third party communication modality. The automated assistant can determine that the user is participating in multiple different conversations via multiple different third party communication services. In some implementations, conversations can be processed to identify particular features of the conversations. When the automated assistant is invoked to provide input to a conversation, the automated assistant can compare the input to the identified conversation features in order to select the particular conversation that is most relevant to the input. In this way, the automated assistant can assist with any of multiple disparate conversations that are each occurring via a different third party application.

Abstract: A computer-implemented method of voice-to-text tagging for transcription of a human voice signal by one of an automatic speech recognition system, or a natural conversation, includes generating a speech-to-text verbal transcript of the verbal vocalizations of an audio signal at a verbal timestamp of the audio signal. A voice-to-text non-verbal transcript of the one or more non-verbal vocalizations of the audio signal is generated at a non-verbal timestamp of the audio signal. The non-verbal transcript and the verbal transcript are combined to generate an enhanced transcript.

Abstract: A computing device trains a position optimization model for determining, from among a plurality of positions, one or more optimal positions on a face based on a training data set including facial skin strain data at the plurality of positions. The computing device trains a speech classification model for classifying a voice from the facial skin strain data based on the training data at the one or more optimal positions determined by the position optimization model among the training data set.

Abstract: Systems and processes for selectively processing and responding to a spoken user input are provided. In one example, audio input containing a spoken user input can be received at a user device. The spoken user input can be identified from the audio input by identifying start and end-points of the spoken user input. It can be determined whether or not the spoken user input was intended for a virtual assistant based on contextual information. The determination can be made using a rule-based system or a probabilistic system. If it is determined that the spoken user input was intended for the virtual assistant, the spoken user input can be processed and an appropriate response can be generated. If it is instead determined that the spoken user input was not intended for the virtual assistant, the spoken user input can be ignored and/or no response can be generated.

Abstract: A method, computer program product and computer system to provide topic guide during document drafting is provided. A processor retrieves at least one section of text from a document. A processor receives a target topic for the document. A processor extracts at least one local topic from the at least one section of text. A processor generates a semantic network comprising the at least one local topic and the target topic. A processor determines a deviation value for the at least one local topic based on a distance between the at least one local topic and the target topic in the semantic network. A processor, in response to the deviation value exceeding a threshold value, alerts a user that the at least one section of text from the document is off-topic from the target topic.

Abstract: Image processing apparatuses have a unit for registering settings in applications or a unit for registering application settings on a portal screen, but do not allow these units to function in a coordinated manner. For example, if a user who frequently uses a certain application registers settings of the application, the settings may also be useful to other users. However, users who mainly use their own portal screens cannot invoke the settings. Settings of an application registered as a shared custom button are automatically registered as frequently used settings in the application. Similarly, settings registered as frequently used settings in an application are automatically registered as a shared custom button.

Abstract: A computer-implemented method, a computer system and a computer program product annotate media files with convenient pause points. The method includes acquiring a text file version of an audio narration file. The text file version includes a pause point history of a plurality of prior users. The method also includes generating a list of pause points based on the pause point history. In addition, the method includes determining a tone of voice being used by a speaker at each pause point using natural language processing algorithms. The method further includes determining a set of convenient pause points based on the list of pause points and the determined tone of voice. Lastly, the method includes inserting the determined set of convenient pause points into the audio narration file.

Abstract: Provided is an acoustic signal processing technique for performing a signal transformation suitable for desired signal processing (e.g., sound source enhancement processing) on a signal, and then performing the desired signal processing on the transformed signal. An acoustic signal processing device performs signal processing M which is a desired target on an input acoustic signal x.

Abstract: The present disclosure generally relates to voice-control for electronic devices. In some embodiments, the method includes, in response to detecting a plurality of utterances, associating the plurality of operations with a first stored operation set and detecting a second set of one or more inputs corresponding to a request to perform the operations associated with the first stored operation set; and performing the plurality of operations associated with the first stored operation set, in the respective order.

Abstract: Described herein are dialog systems, and techniques for providing such dialog systems, that are suitable for use on standalone computing devices. In some embodiments, a dialog system includes a dialog manager, which takes as input an input logical form, which may be a representation of user input. The dialog manager may include a dialog state tracker, an execution subsystem, a dialog policy subsystem, and a context stack. The dialog state tracker may generate an intermediate logical form from the input logical form combined with a context from the context stack. The context stack may maintain a history of a current dialog, and thus, the intermediate logical form may include contextual information potentially missing from the input logical form. The execution subsystem may execute the intermediate logical form to produce an execution result, and the dialog policy subsystem may generate an output logical form based on the execution result.

Abstract: Systems and methods for processing speech transcription in a speech processing system are disclosed. Transcriptions of utterances is received and identifications to the transcriptions are assigned. In response to receiving an indication of an erroneous transcribed utterance in at least one of the transcriptions, an audio receiver is automatically activated for receiving a second utterance. In response to receiving the second utterance, an audio file of the second utterance and a corresponding identification of the erroneous transcribed utterance are transmitted to a speech recognition system for a second transcription, and the erroneous transcribed utterance is replaced with the second transcription.

Abstract: Disclosed are various approaches for generating a text transcript of a soundtrack. The soundtrack can correspond to an event in a conferencing service. Language models can be trained on data that is specific to organizations, users within the organization, and metadata associated with an agenda for the event. The metadata can include texts, attachments, and other data associated with the event. The language models can be arranged into a convolutional neural network and output a text transcript. The text transcript can be used to retrain the language models for subsequent use.