Abstract: A multimode immersion cooling system includes a first, single-phase immersion cooling mode and a second, two-phase immersion cooling mode. The system operates in a single phase mode and reserves a two-phase mode for peak energy consumption periods. A single thermal transfer fluid is used for both modes, remaining in a liquid phase in a first single-phase immersion cooling mode and vaporizing when the thermal transfer fluid temperature reaches its boiling point in a second two-phase immersion cooling mode. A heat exchanger extracts thermal energy from heated thermal transfer fluid in the single phase mode while a condenser cools vaporized thermal transfer fluid to condense the vapor during the second, two-phase immersion cooling mode. A controller determines whether the multimode immersion cooling system operates in the single-phase mode or the second two-phase mode, or both.

Abstract: A robotic garden tool includes at least one sensor configured to generate signals associated with an object within an operating area. A first electronic processor of the robotic garden tool receives, from the at least one sensor, an obstacle signal associated with an obstacle located within the operating area. The first electronic processor determines a first location of the robotic garden tool at a time corresponding to when the first electronic processor received the obstacle signal. The first electronic processor determines a second location of the obstacle based on the obstacle signal and the first location of the garden tool. The first electronic processor generates mapping information of the operating area that includes a virtual boundary based on the second location of the obstacle. The first electronic processor controls the robotic garden tool in the operating area to remain outside of the virtual boundary based on the mapping information.

Abstract: Techniques for generating voice with predetermined emotion type. In an aspect, semantic content and emotion type are separately specified for a speech segment to be generated. A candidate generation module generates a plurality of emotionally diverse candidate speech segments, wherein each candidate has the specified semantic content. A candidate selection module identifies an optimal candidate from amongst the plurality of candidate speech segments, wherein the optimal candidate most closely corresponds to the predetermined emotion type. In further aspects, crowd-sourcing techniques may be applied to generate the plurality of speech output candidates associated with a given semantic content, and machine-learning techniques may be applied to derive parameters for a real-time algorithm for the candidate selection module.

Abstract: Some implementations provide techniques and arrangements for semantic lexicon based processing, such as in an input method editor. In some instances, a semantic label may be received that is to be defined for a semantic lexicon and at least a first term may be identified as a positive or negative example of the semantic label. In response, some examples may label at least a second term in the semantic lexicon with the semantic label based at least in part on the identification of the first term as a positive or negative example of the semantic label.

Abstract: Techniques for generating voice with predetermined emotion type. In an aspect, semantic content and emotion type are separately specified for a speech segment to be generated. A candidate generation module generates a plurality of emotionally diverse candidate speech segments, wherein each candidate has the specified semantic content. A candidate selection module identifies an optimal candidate from amongst the plurality of candidate speech segments, wherein the optimal candidate most closely corresponds to the predetermined emotion type. In further aspects, crowd-sourcing techniques may be applied to generate the plurality of speech output candidates associated with a given semantic content, and machine-learning techniques may be applied to derive parameters for a real-time algorithm for the candidate selection module.

Abstract: New word detection and domain dictionary recommendation are provided. When text content is received according to a given language, for example, Chinese language, words are extracted from the content by analyzing the content according to a variety of rules. The words then are ranked for inclusion into one or more lexicons or domain dictionaries for future use for such functionalities as text input methods, spellchecking, grammar checking, auto entry completion, definition, and the like. In addition, when a user is entering or editing text according to one or more prescribed domain dictionaries, a determination may be made as to whether more helpful domain dictionaries may be available. When entered words have a high degree of association with a given domain dictionary, that domain dictionary may be recommended to the user to increase the accuracy of the user's input of additional text and editing of existing text.

Abstract: New word detection and domain dictionary recommendation are provided. When text content is received according to a given language, for example, Chinese language, words are extracted from the content by analyzing the content according to a variety of rules. The words then are ranked for inclusion into one or more lexicons or domain dictionaries for future use for such functionalities as text input methods, spellchecking, grammar checking, auto entry completion, definition, and the like. In addition, when a user is entering or editing text according to one or more prescribed domain dictionaries, a determination may be made as to whether more helpful domain dictionaries may be available. When entered words have a high degree of association with a given domain dictionary, that domain dictionary may be recommended to the user to increase the accuracy of the user's input of additional text and editing of existing text.

Abstract: Techniques for interactively presenting word-alignments of multilingual translations and automatically improving those translations based upon user feedback are described herein. With one or more implementations of the techniques described herein, a word-alignment user-interface (UI) concurrently displays a pair of bilingual sentences, where one is a translation of the other, and interactively highlights linked (i.e., “word-aligned”) words and phrases of the pair. Other implementations of the techniques described herein offer an option for a user to provide feedback about the existing word-alignments or realign the words or phrases. In still other described implementations, word-alignment is automatically improved based upon that user feedback.

Abstract: Some implementations provide techniques and arrangements for semantic lexicon based processing, such as in an input method editor. In some instances, a semantic label may be received that is to be defined for a semantic lexicon and at least a first term may be identified as a positive or negative example of the semantic label. In response, some examples may label at least a second term in the semantic lexicon with the semantic label based at least in part on the identification of the first term as a positive or negative example of the semantic label.

Abstract: Processing video for utilization in second language learning is described herein. A video file includes spoken words in a source language, subtitles in the source language, and subtitles in a native language of an end user (a target language). The subtitles in the source language are synchronized with the spoken words in the video, and the subtitles in the source language are mapped to the subtitles in the target language. Both sets of subtitles are displayed simultaneously as the video is played by the end user.

Abstract: New word detection and domain dictionary recommendation are provided. When text content is received according to a given language, for example, Chinese language, words are extracted from the content by analyzing the content according to a variety of rules. The words then are ranked for inclusion into one or more lexicons or domain dictionaries for future use for such functionalities as text input methods, spellchecking, grammar checking, auto entry completion, definition, and the like. In addition, when a user is entering or editing text according to one or more prescribed domain dictionaries, a determination may be made as to whether more helpful domain dictionaries may be available. When entered words have a high degree of association with a given domain dictionary, that domain dictionary may be recommended to the user to increase the accuracy of the user's input of additional text and editing of existing text.

Abstract: Processing video for utilization in second language learning is described herein. A video file includes spoken words in a source language, subtitles in the source language, and subtitles in a native language of an end user (a target language). The subtitles in the source language are synchronized with the spoken words in the video, and the subtitles in the source language are mapped to the subtitles in the target language. Both sets of subtitles are displayed simultaneously as the video is played by the end user.

Abstract: Processing video for utilization in second language learning is described herein. A video file includes spoken words in a source language, subtitles in the source language, and subtitles in a native language of an end user (a target language). The subtitles in the source language are synchronized with the spoken words in the video, and the subtitles in the source language are mapped to the subtitles in the target language. Both sets of subtitles are displayed simultaneously as the video is played by the end user.

Abstract: A method of statistical machine translation (SMT) is provided. The method comprises generating reordering knowledge based on the syntax of a source language (SL) and a number of alignment matrices that map sample SL sentences with sample target language (TL) sentences. The method further comprises receiving a SL word string and parsing the SL word string into a parse tree that represents the syntactic properties of the SL word string. The nodes on the parse tree are reordered based on the generated reordering knowledge in order to provide reordered word strings. The method further comprises translating a number of reordered word strings to create a number of TL word strings, and identifying a statistically preferred TL word string as a preferred translation of the SL word string.

Abstract: A method of statistical machine translation (SMT) is provided. The method comprises generating reordering knowledge based on the syntax of a source language (SL) and a number of alignment matrices that map sample SL sentences with sample target language (TL) sentences. The method further comprises receiving a SL word string and parsing the SL word string into a parse tree that represents the syntactic properties of the SL word string. The nodes on the parse tree are reordered based on the generated reordering knowledge in order to provide reordered word strings. The method further comprises translating a number of reordered word strings to create a number of TL word strings, and identifying a statistically preferred TL word string as a preferred translation of the SL word string.

Abstract: A method of statistical machine translation (SMT) is provided. The method comprises generating reordering knowledge based on the syntax of a source language (SL) and a number of alignment matrices that map sample SL sentences with sample target language (TL) sentences. The method further comprises receiving a SL word string and parsing the SL word string into a parse tree that represents the syntactic properties of the SL word string. The nodes on the parse tree are reordered based on the generated reordering knowledge in order to provide reordered word strings. The method further comprises translating a number of reordered word strings to create a number of TL word strings, and identifying a statistically preferred TL word string as a preferred translation of the SL word string.