Abstract: Systems and techniques for acoustic-based linguistically-driven automated text formatting of acoustic input are described herein. An audio sample may be obtained that includes multiple words from human speech. The audio sample may be processed to determine a linguistic relationship of the words from the acoustic properties of the words. Based on the determined linguistic relationships, data such as an acoustical language model is generated to enable an arrangement of the words into a cascade format (e.g., a cascade format that establishes horizontal displacement and vertical displacement among the multiple words). A cascaded text output may be provided from the acoustical language model or other types of related data.

Abstract: Systems and techniques for linguistic learning using automatically cascaded text are described herein. A data model is generated to identify linguistic relationships among respective words and word groups in a source text. The data model is augmented with linguistic properties associated with individual words in the source text. An arrangement of cascaded text is determined based on the linguistic relationships identified in the data model. The arrangement of cascaded text includes horizontal displacement and vertical displacement for the respective words and word groups. Display enhancements to the arrangement of cascaded text are determined wherein the display enhancements are based on user-selected options to show visual aids that identify the linguistic relationships among the respective words and word groups or linguistic properties associated with individual words. The arrangement of cascaded text and the display enhancements are output in a user interface.

Abstract: Various examples of approaches for using and implementing cascaded text formatting within electronic publishing and display mediums are described herein. In an example, a method for analyzing and re-formatting a stream of text, includes: obtaining a stream of human-readable text in a natural language processing (NLP) parser to identify parts-of-speech and key phrases in a proper sentence; tagging the identified parts-of-speech according to the respective parts and key phrases; generating a text cascade arrangement for a display of the proper sentence by applying predefined rules to the part-of-speech and key phrases, where such a display of the proper sentence provides breaks and cascading, including indentations, according to the pre-defined rules; and outputting an electronic display of the proper sentence which includes the text cascade arrangement.

Abstract: Systems and techniques for acoustic-based linguistically-driven automated text formatting of acoustic input are described herein. An audio sample may be obtained that includes multiple words from human speech. The audio sample may be processed to determine a linguistic relationship of the words from the acoustic properties of the words. Based on the determined linguistic relationships, data such as an acoustical language model is generated to enable an arrangement of the words into a cascade format (e.g., a cascade format that establishes horizontal displacement and vertical displacement among the multiple words). A cascaded text output may be provided from the acoustical language model or other types of related data.

Abstract: Systems and techniques for linguistically-driven automated text formatting are described herein. Data representing the linguistic structure of input text may be received from Natural Language Processing (NLP) Services, including but not limited to constituents, dependencies, and coreference relationships. A text model of the input text may be built using the linguistic components and relationships. Cascade rules may be applied to the text model to generate a cascaded text data structure. Cascaded data may be displayed on a range of media, including a phone, tablet, laptop, monitor, VR/AR devices. Cascaded data may be presented in dual screen formats to promote more accurate and efficient reading comprehension, greater ease in teaching native and foreign language grammatical structures, and tools for remediation of reading-related disabilities.

Abstract: Systems and techniques for linguistically-driven automated text formatting are described herein. Data representing the linguistic structure of input text may be received from Natural Language Processing (NLP) Services, including but not limited to constituents, dependencies, and coreference relationships. A text model of the input text may be built using the linguistic components and relationships. Cascade rules may be applied to the text model to generate a cascaded text data structure. Cascaded data may be displayed on a range of media, including a phone, tablet, laptop, monitor, VR/AR devices. Cascaded data may be presented in dual screen formats to promote more accurate and efficient reading comprehension, greater ease in teaching native and foreign language grammatical structures, and tools for remediation of reading-related disabilities.

Abstract: Various examples of approaches for using and implementing cascaded text formatting within electronic publishing and display mediums are described herein. In an example, a method for analyzing and re-formatting a stream of text, includes: obtaining a stream of human-readable text in a natural language processing (NLP) parser to identify parts-of-speech and key phrases in a proper sentence; tagging the identified parts-of-speech according to the respective parts and key phrases; generating a text cascade arrangement for a display of the proper sentence by applying predefined rules to the part-of-speech and key phrases, where such a display of the proper sentence provides breaks and cascading, including indentations, according to the pre-defined rules; and outputting an electronic display of the proper sentence which includes the text cascade arrangement.

Abstract: Systems and techniques for linguistically-driven automated text formatting are described herein. Data representing the linguistic structure of input text may be received from Natural Language Processing (NLP) Services, including but not limited to constituents, dependencies, and coreference relationships. A text model of the input text may be built using the linguistic components and relationships. Cascade rules may be applied to the text model to generate a cascaded text data structure. Cascaded data may be displayed on a range of media, including a phone, tablet, laptop, monitor, VR/AR devices. Cascaded data may be presented in dual screen formats to promote more accurate and efficient reading comprehension, greater ease in teaching native and foreign language grammatical structures, and tools for remediation of reading-related disabilities.

Abstract: Systems and techniques for linguistically-driven automated text formatting are described herein. Data representing the linguistic structure of input text may be received from Natural Language Processing (NLP) Services, including but not limited to constituents, dependencies, and coreference relationships. A text model of the input text may be built using the linguistic components and relationships. Cascade rules may be applied to the text model to generate a cascaded text data structure. Cascaded data may be displayed on a range of media, including a phone, tablet, laptop, monitor, VR/AR devices. Cascaded data may be presented in dual screen formats to promote more accurate and efficient reading comprehension, greater ease in teaching native and foreign language grammatical structures, and tools for remediation of reading-related disabilities.

Abstract: A mobile and web-based personal goal system for families that rewards children or other family members for completing tasks in the areas of academics, health, finances and money, family, and community. The system offers families a consistent way to interact offline and online regarding children's choices and a way to reward them for those choices. Multiple children can be members of one family account, frequently referred to as a sponsor account.