Abstract: The disclosure describes a generalized system and method to incorporate speak-n-touch UI and multi-sense UI into applications. Several examples are considered. Additionally, several new user experiences across a variety of applications are also presented. Our approach has potential to shift the interface paradigm and propel a new wave of artificial intelligence based general purpose computing.

Abstract: The disclosure describes keyboard user-interfaces UIs. A system including a modified keyboard having fewer keys than a standard qwerty keyboard is disclosed. The modified keyboard appears on a display of the system. The system also including a keyboard UI module for processing inputs from the modified keyboard, wherein the keyboard UI module implements directional double taps for specified symbols, swipe gestures for changing modes that are displayed as the modified keyboard and for incorporating special keys of the modified keyboard, and status indicator changes using color coding schemes on the display. The keyboard UI module for implements wavetags for blind input of symbols and shortcuts on the modified keyboard.

Abstract: The disclosure describes an overall system and method for designing and building multi-sense systems using a generalized synchrony based fusion technique. By treating “time” as a common thread that runs across all the modes, the invention uses trigger inputs to form several groups of inputs across all modes. The best group is selected as the one that has the maximize synchrony as determined by a combination of a weight for the group and a timing correlation of inputs within that group. The features from each mode within the best group are then used individually or jointly for pattern recognition or understanding. The result is a robust practically implementable generalized theory of multi-sense fusion. The proposed invention has immense potential to leap frog single input systems and revolutionize human-machine interactions.

Abstract: The disclosure describe a system and method for detecting one or more segments of desired speech utterances from an audio stream using timings of events from other modes that are correlated to the timings of the desired segments of speech. The redundant information from other modes results in a highly accurate and robust utterance detection.

Abstract: The disclosure describes an overall system/method for developing a “speak and touch auto correction interface” referred to as STACI which is far more superior to existing user interfaces including the widely adopted qwerty. Using STACI a user speaks and types a word at the same time. The redundant information from the two modes, namely speech and the letters typed, enables the user to sloppily and partially type the words. The result is a very fast and accurate enhanced keyboard interface enabling document production on computing devices like phones and tablets.

Abstract: The disclosure describe a system and method for detecting one or more segments of desired speech utterances from an audio stream using timings of events from other modes that are correlated to the timings of the desired segments of speech. The redundant information from other modes results in a highly accurate and robust utterance detection.

Abstract: The disclosure describes a speech detection system for detecting one or more desired speech segments in an audio stream. The speech detection system includes an audio stream input and a speech detection technique. The speech detection technique may be performed in various ways, such as using pattern matching and/or signal processing. The pattern matching implementation may extract features representing types of sounds as in phrases, words, syllables, phonemes and so on. The signal processing implementation may extract spectrally-localized frequency-based features, amplitude-based features, and combinations of the frequency-based and amplitude-based features. Metrics may be obtained and used to determine a desired word in the audio stream. In addition, a keypad stream having keypad entries may be used in determining the desired word.

Abstract: The disclosure describes an overall system/method for developing a “speak and touch auto correction interface” referred to as STACI which is far more superior to existing user interfaces including the widely adopted qwerty. Using STACI a user speaks and types a word at the same time. The redundant information from the two modes, namely speech and the letters typed, enables the user to sloppily and partially type the words. The result is a very fast and accurate enhanced keyboard interface enabling document production on computing devices like phones and tablets.

Abstract: The disclosure describes an overall system/method for text-input using a multimodal interface with a combination of speech recognition and text prediction. Specifically, an “always listening” mode for entering words is combined with a push-to-speak mode for entering symbols and phrases. In addition, these two modes are further combined with keypad based text prediction. Finally, the overall user-interface of the proposed system is designed such that it enhances existing standard text-input methods; thereby minimizing the behavior change for mobile users.

Abstract: The disclosure describes an overall system/method for text-input using a multimodal interface with speech recognition. Specifically, pluralities of modes interact with the main speech mode to provide the speech-recognition system with partial knowledge of the text corresponding to the spoken utterance forming the input to the speech recognition system. The knowledge from other modes is used to dynamically change the ASR system's active vocabulary thereby significantly increasing recognition accuracy and significantly reducing processing requirements. Additionally, the speech recognition system is configured using three different system configurations (always listening, partially listening, and push-to-speak) and for each one of those three different user-interfaces are proposed (speak-and-type, type-and-speak, and speak-while-typing).

Abstract: This disclosure describes a practical system/method for predicting spoken text (a spoken word or a spoken sentence/phrase) given that text's partial spelling (example, initial characters forming the spelling of a word/sentence). The partial spelling may be given using “Speech” or may be inputted using the keyboard/keypad or may be obtained using other input methods. The disclosed system is an alternative method for inputting text into devices; the method is faster (especially for long words or phrases) compared to existing predictive-text-input and/or word-completion methods.

Abstract: The disclosure describes a speech detection system for detecting one or more desired speech segments in an audio stream. The speech detection system includes an audio stream input and a speech detection technique. The speech detection technique may be performed in various ways, such as using pattern matching and/or signal processing. The pattern matching implementation may extract features representing types of sounds as in phrases, words, syllables, phonemes and so on. The signal processing implementation may extract spectrally-localized frequency-based features, amplitude-based features, and combinations of the frequency-based and amplitude-based features. Metrics may be obtained and used to determine a desired word in the audio stream. In addition, a keypad stream having keypad entries may be used in determining the desired word.

Abstract: The disclosure describes an overall system/method for text-input using a multimodal interface with a combination of speech recognition and text prediction. Specifically, an “always listening” mode for entering words is combined with a push-to-speak mode for entering symbols and phrases. In addition, these two modes are further combined with keypad based text prediction. Finally, the overall user-interface of the proposed system is designed such that it enhances existing standard text-input methods; thereby minimizing the behavior change for mobile users.

Abstract: The disclosure describes an overall system/method for text-input using a multimodal interface with speech recognition. Specifically, pluralities of modes interact with the main speech mode to provide the speech-recognition system with partial knowledge of the text corresponding to the spoken utterance forming the input to the speech recognition system. The knowledge from other modes is used to dynamically change the ASR system's active vocabulary thereby significantly increasing recognition accuracy and significantly reducing processing requirements. Additionally, the speech recognition system is configured using three different system configurations (always listening, partially listening, and push-to-speak) and for each one of those three different user-interfaces are proposed (speak-and-type, type-and-speak, and speak-while-typing).

Abstract: This disclosure describes a practical system/method for predicting spoken text (a spoken word or a spoken sentence/phrase) given that text's partial spelling (example, initial characters forming the spelling of a word/sentence). The partial spelling may be given using “Speech” or may be inputted using the keyboard/keypad or may be obtained using other input methods. The disclosed system is an alternative method for inputting text into devices; the method is faster (especially for long words or phrases) compared to existing predictive-text-input and/or word-completion methods.