Abstract: A method and system for identifying enhancement suggestions for a document and displaying the identified suggestions in a user-friendly manner may include examining the document to identify an enhancement fora portion of content in the document, enabling display of a first user interface element for previewing the identified enhancement as applied to the content, receiving a request to select the identified enhancement, and upon receiving the request enabling display of a second user interface element for accepting the identified enhancement. The first user interface element may provide a preview of the document post enhancement.

Abstract: A data processing system implements displaying, on a first device to a first participant, a first user interface for presentation of audio content, the first user interface including a navigation tool configured to visually represent contextual events in the audio content and a first selectable indicator linked to a second participant. The data processing system further implements receiving a first user selection of the first selectable indicator; and initiating, in response to at least the first user selection, a first telecommunication session between the first participant and the second participant.

Abstract: A method and system for identifying enhancement suggestions for a document and displaying the identified suggestions in a user-friendly manner may include examining the document to identify an enhancement fora portion of content in the document, enabling display of a first user interface element for previewing the identified enhancement as applied to the content, receiving a request to select the identified enhancement, and upon receiving the request enabling display of a second user interface element for accepting the identified enhancement. The first user interface element may provide a preview of the document post enhancement.

Abstract: Techniques performed by a data processing system for processing voice content received from a user herein include receiving a first audio input from a user comprising spoken content, analyzing the first audio input using one or more natural language processing models to produce a first textual output comprising a textual representation of the first audio input, analyzing the first textual output using one or more machine learning models to determine first context information of the first textual output, and processing the first textual output in the application based on the first context information.

Abstract: A data processing system implements displaying, on a first device to a first participant, a first user interface for presentation of audio content, the first user interface including a navigation tool configured to visually represent contextual events in the audio content and a first selectable indicator linked to a second participant. The data processing system further implements receiving a first user selection of the first selectable indicator; and initiating, in response to at least the first user selection, a first telecommunication session between the first participant and the second participant.

Abstract: An audio-visual management system and process for facilitating comprehension of electronic documents. As an example, a user may access contents of an electronic document via a user interface and request a speech-synthesized recitation of any text in the electronic document. In addition, the user interface can include a navigation tool configured to visually represent significant events in the electronic document via selectable indicators, including but not limited to comments, slides, images, graphs, and/or other internal contextual markers. These indicators can serve as navigation options that can provide guidance to users as they listen to a reading of the electronic document. User selection of an indicator can initiate an audio presentation of textual content that is directly associated with the specified event. In addition, users can view availability of others currently listening to the document and connect with them to create a joint listening experience.

Abstract: Techniques performed by a data processing system for processing voice content received from a user herein include receiving a first audio input from a user comprising spoken content, analyzing the first audio input using one or more natural language processing models to produce a first textual output comprising a textual representation of the first audio input, analyzing the first textual output using one or more machine learning models to determine first context information of the first textual output, and processing the first textual output in the application based on the first context information.

Abstract: The systems and techniques disclosed here feature a device including an audio analyzer connected to microphone(s) monitoring a conversation between one or more individuals. The audio analyzer can identify auditory expressions from audio captured by the microphone, where the auditory expressions can include linguistic expressions and nonlinguistic expressions. The audio analyzer can analyze the linguistic expressions to identify a topic and a time period when the topic was discussed. A video analyzer can be connected to camera(s) monitoring the conversation. The video analyzer can identify non-auditory expressions by the individuals from video captured by the camera. A sentiment analyzer can analyze auditory expressions during the time period when the topic was discussed and non-auditory expressions during the time period when the topic was discussed to determine sentiments to the topic. A processor can analyze the determined sentiments to the topic to determine a group sentiment to the topic.

Abstract: The systems and techniques disclosed here feature a device including an audio analyzer connected to microphone(s) monitoring a conversation between one or more individuals. The audio analyzer can identify auditory expressions from audio captured by the microphone, where the auditory expressions can include linguistic expressions and nonlinguistic expressions. The audio analyzer can analyze the linguistic expressions to identify a topic and a time period when the topic was discussed. A video analyzer can be connected to camera(s) monitoring the conversation. The video analyzer can identify non-auditory expressions by the individuals from video captured by the camera. A sentiment analyzer can analyze auditory expressions during the time period when the topic was discussed and non-auditory expressions during the time period when the topic was discussed to determine sentiments to the topic. A processor can analyze the determined sentiments to the topic to determine a group sentiment to the topic.

Abstract: An audio-visual management system and process for facilitating comprehension of electronic documents. As an example, a user may access contents of an electronic document via a user interface and request a speech-synthesized recitation of any text in the electronic document. In addition, the user interface can include a navigation tool configured to visually represent significant events in the electronic document via selectable indicators, including but not limited to comments, slides, images, graphs, and/or other internal contextual markers. These indicators can serve as navigation options that can provide guidance to users as they listen to a reading of the electronic document. User selection of an indicator can initiate an audio presentation of textual content that is directly associated with the specified event. In addition, users can view availability of others currently listening to the document and connect with them to create a joint listening experience.

Abstract: Examples described herein improve the way in which a transcript is generated and displayed so that the context of a conversation taking place during a meeting or another type of collaboration event can be understood by a person that reviews the transcript (e.g., reads or browses through the transcript). The techniques described herein use voice recognition to identify a user that is speaking during the meeting. Accordingly, when the speech of the user is converted to text for the transcript, the text can be attributed to the identified user. The techniques described herein further configure a graphical user interface layout, in which the transcript can be displayed. The graphical user interface layout enables users to better understand the context of a conversation that takes place during a meeting.

Abstract: Examples described herein improve the way in which a transcript is generated and displayed so that the context of a conversation taking place during a meeting or another type of collaboration event can be understood by a person that reviews the transcript (e.g., reads or browses through the transcript). The techniques described herein use voice recognition to identify a user that is speaking during the meeting. Accordingly, when the speech of the user is converted to text for the transcript, the text can be attributed to the identified user. The techniques described herein further configure a graphical user interface layout, in which the transcript can be displayed. The graphical user interface layout enables users to better understand the context of a conversation that takes place during a meeting.