Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. An example system includes processor circuitry to generate a breathing cue to enhance speech to be synthesized from text; determine a first insertion point of the breathing cue in the text, wherein the breathing cue is identified by a first tag of a markup language; generate a prosody cue to enhance speech to be synthesized from the text; determine a second insertion point of the prosody cue in the text, wherein the prosody cue is identified by a second tag of the markup language; insert the breathing cue at the first insertion point based on the first tag and the prosody cue at the second insertion point based on the second tag; and trigger a synthesis of the speech from the text, the breathing cue, and the prosody cue.

Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. An example system includes processor circuitry to generate a breathing cue to enhance speech to be synthesized from text; determine a first insertion point of the breathing cue in the text, wherein the breathing cue is identified by a first tag of a markup language; generate a prosody cue to enhance speech to be synthesized from the text; determine a second insertion point of the prosody cue in the text, wherein the prosody cue is identified by a second tag of the markup language; insert the breathing cue at the first insertion point based on the first tag and the prosody cue at the second insertion point based on the second tag; and trigger a synthesis of the speech from the text, the breathing cue, and the prosody cue.

Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. An example system includes processor circuitry to generate a breathing cue to enhance speech to be synthesized from text; determine a first insertion point of the breathing cue in the text, wherein the breathing cue is identified by a first tag of a markup language; generate a prosody cue to enhance speech to be synthesized from the text; determine a second insertion point of the prosody cue in the text, wherein the prosody cue is identified by a second tag of the markup language; insert the breathing cue at the first insertion point based on the first tag and the prosody cue at the second insertion point based on the second tag; and trigger a synthesis of the speech from the text, the breathing cue, and the prosody cue.

Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. An example system includes one or more storage devices including instructions and a processor to execute the instructions. The processor is to execute the instructions to: determine a user tone of the user input; generate a response to the user input based on the user tone; and identify a response tone associated with the user tone. The example system also includes a transmitter to communicate the response and the response tone over a network.

Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. An example system includes one or more storage devices including instructions and a processor to execute the instructions. The processor is to execute the instructions to: generate first and second non-lexical cues to enhance speech to be synthesized from text; determine a first insertion point of the first non-lexical cue in the text; determine a second insertion point of the second non-lexical cue in the text; and insert the first non-lexical cue at the first insertion point and the second non-lexical cue at the second insertion point. The example system also includes a transmitter to communicate the text with the inserted first non-lexical cue and the inserted second non-lexical cue over a network.

Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. An example system includes one or more storage devices including instructions and a processor to execute the instructions. The processor is to execute the instructions to: determine a user tone of the user input; generate a response to the user input based on the user tone; and identify a response tone associated with the user tone. The example system also includes a transmitter to communicate the response and the response tone over a network.

Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. An example system includes one or more storage devices including instructions and a processor to execute the instructions. The processor is to execute the instructions to: generate first and second non-lexical cues to enhance speech to be synthesized from text; determine a first insertion point of the first non-lexical cue in the text; determine a second insertion point of the second non-lexical cue in the text; and insert the first non-lexical cue at the first insertion point and the second non-lexical cue at the second insertion point. The example system also includes a transmitter to communicate the text with the inserted first non-lexical cue and the inserted second non-lexical cue over a network.

Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. Original text is analyzed to determine characteristics of the text and/or to derive or augment an intent (e.g., an intent code). Non-lexical cue insertion points are determined based on the characteristics of the text and/or the intent. One or more non-lexical cues are inserted at insertion points to generate augmented text. The augmented text is synthesized into speech, including converting the non-lexical cues to speech output.

Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. Original text is analyzed to determine characteristics of the text and/or to derive or augment an intent (e.g., an intent code). Non-lexical cue insertion points are determined based on the characteristics of the text and/or the intent. One or more non-lexical cues are inserted at insertion points to generate augmented text. The augmented text is synthesized into speech, including converting the non-lexical cues to speech output.

Abstract: Embodiments are directed to systems, methods, and devices for providing help to a user through an output modality. Embodiments include an analysis logic implemented at least partially in hardware to receive an indication to provide help or other information to the user; identify an availability of one or more output modalities for providing the help; and determine an output modality for providing the help based on the availability of the one or more output modalities. Embodiments also include a dialog system implemented at least partially in hardware to process the request for help; and provide a dialog message in response to the request for help, the dialog message provided on the determined output modality. Some embodiments also include a sensor input for receiving sensory information, wherein the analysis logic identifies the output modality based, at least in part, on the sensory information.

Abstract: Systems and methods may provide non-lexical cues in synthesized speech. A system may generate response text and a response intent based on user input. Non-lexical cue insertion points are determined based on the characteristics of the text and/or the intent. One or more non-lexical cues are inserted at insertion points to generate augmented text. The augmented text is synthesized into speech using speech units associated with the response text and the inserted response intent.

Abstract: Embodiments are directed to systems, methods, and devices that are directed to a sensor implemented at least partially in hardware to detect information about a user and a processor implemented at least partially in hardware to determine a state of the user based on the detected information, and select an output mode for a dialog message based on the state of the user. A dialog system implemented at least partially in hardware can be included to configure a dialog message based on the selected output mode; and output the dialog message to the user.

Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. Original text is analyzed to determine characteristics of the text and/or to derive or augment an intent (e.g., an intent code). Non-lexical cue insertion points are determined based on the characteristics of the text and/or the intent. One or more non-lexical cues are inserted at insertion points to generate augmented text. The augmented text is synthesized into speech, including converting the non-lexical cues to speech output.

Abstract: A method is described to facilitate coaching feedback adjustment. The method includes generating feedback for a user, receiving contextual data at a sensor array, determining a context based on contextual conditions identified from the contextual data, determining an action to be taken based on the identified contextual conditions, determining whether the feedback is appropriate based on the action to be taken and the contextual conditions and playing the feedback upon a determination that the feedback is appropriate.

Abstract: Systems and methods for providing non-lexical cues in synthesized speech are described herein. Original text is analyzed to determine characteristics of the text and/or to derive or augment an intent (e.g., an intent code). Non-lexical cue insertion points are determined based on the characteristics of the text and/or the intent. One or more nonlexical cues are inserted at insertion points to generate augmented text. The augmented text is synthesized into speech, including converting the non-lexical cues to speech output.

Abstract: Systems and methods for providing a user adaptive natural language interface are disclosed. The disclosed embodiments may receive and analyze user input to derive current user behavior data, including data indicative of characteristics of the user input. The user input is classified based on prior user behavior data previously logged during one or more previous user-system interactions and the current user behavior data to generate a classification of the user input. Machine learning algorithms can be employed to classify the user input. User adaptive utterances are selected based on the user input and the classification of the user input. The user-system interaction is logged for use as prior user behavior data in future user-system interactions. A response to the user input is generated, including synthesizing output speech from the user adaptive utterances selected. Example applications of the disclosed systems and methods provide user adaptive navigation directions in navigation systems.

Abstract: Systems and methods are disclosed for providing non-lexical cues in synthesized speech. Original text is analyzed to determine characteristics of the text and/or to derive or augment an intent (e.g., an intent code). Non-lexical cue insertion points are determined based on the characteristics of the text and/or the intent. One or more non-lexical cues are inserted at insertion points to generate augmented text. The augmented text is synthesized into speech, including converting the non-lexical cues to speech output.