Abstract: An apparatus for speech model with personalization via ambient context harvesting, is described herein. The apparatus includes a microphone, context harvesting module, confidence module, and training module. The context harvesting module is to determine a context associated with the captured audio signals. A confidence module is to determine a confidence of the context as applied to the audio signals. A training module is to train a neural network in response to the confidence being above a predetermined threshold.

Abstract: An apparatus for speech model with personalization via ambient context harvesting, is described herein. The apparatus includes a microphone, context harvesting module, confidence module, and training module. The context harvesting module is to determine a context associated with the captured audio signals. A confidence module is to determine a confidence of the context as applied to the audio signals. A training module is to train a neural network in response to the confidence being above a predetermined threshold.

Abstract: Systems, methods, and apparatus for providing accessible user interfaces are disclosed. An example apparatus includes a display region analyzer to identify one or more of text or graphics in display frame image data, the display frame image data corresponding to a portion of a display frame associated with a touch event on a display screen of an electronic device; an audio controller interface to transmit, in response to the identification of the text in the display frame image data, an instruction including audio output corresponding to the text to be output by the electronic device; and a haptic feedback controller interface to transmit, in response to the identification of the graphics in the display frame image data, an instruction including a haptic feedback response to be output by the electronic device.

Abstract: Computing platforms and related methods for providing accessible user interfaces are disclosed. An example apparatus includes a display controller to a display controller to sample a region of a display frame associated with a location of a touch on a display screen of a user device and logic circuitry to, after a Basic Input Output System (BIOS) is operational in the user device and prior to loading of an operating system of the user device, identify content in the display region and cause at least one output device to generate an output representative of the content, the output including at least one of an audible output or a haptic output.

Abstract: An apparatus for speech model with personalization via ambient context harvesting, is described herein. The apparatus includes a microphone, context harvesting module, confidence module, and training module. The context harvesting module is to determine a context associated with the captured audio signals. A confidence module is to determine a confidence of the context as applied to the audio signals. A training module is to train a neural network in response to the confidence being above a predetermined threshold.

Abstract: Systems, apparatus and methods are described including operations for a dual mode GMM (Gaussian Mixture Model) scoring accelerator for both speech and video data.

Abstract: A language model is modified for a local speech recognition system using remote speech recognition sources. In one example, a speech utterance is received. The speech utterance is sent to at least one remote speech recognition system. Text results corresponding to the utterance are received from the remote speech recognition system. A local text result is generated using local vocabulary. The received text results and the generated text result are compared to determine words that are out of the local vocabulary and the local vocabulary is updated using the out of vocabulary words.

Abstract: Systems, apparatus and methods are described including operations for a dual mode GMM (Gaussian Mixture Model) scoring accelerator for both speech and video data.

Abstract: A language model is modified for a local speech recognition system using remote speech recognition sources. In one example, a speech utterance is received. The speech utterance is sent to at least one remote speech recognition system. Text results corresponding to the utterance are received from the remote speech recognition system. A local text result is generated using local vocabulary. The received text results and the generated text result are compared to determine words that are out of the local vocabulary and the local vocabulary is updated using the out of vocabulary words.

Abstract: Systems and techniques to reduce noise in audio information. According to an aspect, the technique includes determining a speech-presence-uncertainty metric based on input representing audio information, and performing smoothing during noise suppression of the input information based on the determined speech-presence-uncertainty metric to produce output representing audio information with enhanced speech and reduced musical noise. According to another aspect, the system includes speech presence uncertainty assessment circuitry that determines a speech-presence-uncertainty metric based on input audio information and filter coefficients, and smoothing circuitry including a filter (e.g., a low-pass filter) coupled to receive the filter coefficients and a multiplier unit coupled to receive the input audio information and output filter coefficients from the filter.