Abstract: Systems and methods for utilizing level differences to attenuate noise and enhance speech are provided. In exemplary embodiments, energy estimates of acoustic signals, representing captured sound, are determined in order to determine a level difference. This level difference in combination with a noise estimate, based only on a primary acoustic signal, allow a filter estimate to be derived. In some embodiments, the derived filter estimate may be smoothed. The filter estimate is then applied to the acoustic signal from the primary acoustic signal to generate a speech estimate.

Abstract: Provided are systems and methods for image enhancement based on combining multiple related images, such as images of the same object taken from different imaging angles. This approach allows simulating images captured from longer distances using telephoto lenses. Initial images may be captured using a simple camera equipped with shorter focal length lenses, typically used on camera phones, tablets, and laptops. The initial images may be taken using a single camera. An object or, more specifically, a center line of the object is identified in each image. The object is typically present in the foreground portion of the initial images. The initial images may be cross-faded along the object center line to yield a combined image. Separating of the foreground and background portions of each image may be separated and separately processed, such as blurring the background portion and sharpening the foreground portion.

Abstract: Provided are systems and methods for image enhancement based on combining multiple related images, such as images of the same object taken from different imaging angles. This approach allows simulating images captured from longer distances using telephoto lenses. Initial images may be captured using simple cameras equipped with shorter focal length lenses, typically used on camera phones, tablets, and laptops. The initial images may be taken using two different cameras positioned a certain distance from each other. An object or, more specifically, a center line of the object is identified in each image. The object is typically present in the foreground portion of the initial images. The initial images may be cross-faded along the object center line to yield a combined image. Separating of the foreground and background portions of each image may be separated and separately processed, such as blurring the background portion and sharpening the foreground portion.

Abstract: Systems and methods for utilizing inter-microphone level differences to attenuate noise and enhance speech are provided. In exemplary embodiments, energy estimates of acoustic signals received by a primary microphone and a secondary microphone are determined in order to determine an inter-microphone level difference (ILD). This ILD in combination with a noise estimate based only on a primary microphone acoustic signal allow a filter estimate to be derived. In some embodiments, the derived filter estimate may be smoothed. The filter estimate is then applied to the acoustic signal from the primary microphone to generate a speech estimate.

Abstract: Provided are computer-implemented systems and methods for image correction after combining images from multiple cameras. While combining multiple images may significantly enhance image quality without a need for a longer focal length lens, combined images may have some perspective distortion caused by different imaging angles used by different cameras. For example, when two cameras provided on the same device are used to capture images of a face and these images are combined by cross-fading, a combined image may have an unnaturally widened center portion. Specifically, proportions of nose and ears may be distorted resulting in a wider nose and generally a wider face. The combined image may be compressed either uniformly or non-uniformly (e.g., more compression in the center) to yield a processed image with more realistic and/or natural proportions. The compression ratio and/or compression distribution may depend on imaging angles, various distances, and other factors described herein.

Abstract: Background audio can be provided during telephonic communication. Telephonic communication can be established via a network, such as between a user of a telephony device and a communication partner having a second telephony device. A voice signal may be received from the user via a microphone integral with the telephony device. An audio track can be retrieved, for example, from memory integral with the telephony device or from a third-party service provider via the communications network. Noise reduction is performed on the voice signal to produce a clean voice signal. The clean voice signal may be combined with the audio track to produce a combined signal, such that the audio track provides background audio to the clean voice signal. The combined signal can then be transmitted from the telephony device to the second telephony device via the communications network.

Abstract: Provided are systems and methods for image enhancement based on combining multiple related images, such as images of the same object taken from different imaging angles. This approach allows simulating images captured from longer distances using telephoto lenses. Initial images may be captured using simple cameras equipped with shorter focal length lenses, typically used on camera phones, tablets, and laptops. The initial images may be taken using two different cameras positioned a certain distance from each other. An object or, more specifically, a center line of the object is identified in each image. The object is typically present in the foreground portion of the initial images. The initial images may be cross-faded along the object center line to yield a combined image. Separating of the foreground and background portions of each image may be separated and separately processed, such as blurring the background portion and sharpening the foreground portion.

Abstract: Provided are computer-implemented systems and methods for image enhancement using one or more image processing techniques, such as stereo disparity, facial recognition, and other like features. An image may be captured using one or two cameras provided on the same device. The image is then processed to detect at least one of a foreground portion or a background portion of the image. These portions are then processed independently from each other, for example, to enhance the foreground and/or blur the background. For example, a circular blur or a Gaussian blur technique may be applied to the background. The processing may be performed on still images and/or video images, such as live teleconferences. The processing may be performed on an image capturing device, such as a mobile phone, a tablet computer, or a laptop computer, or performed on a back-end system.

Abstract: Systems and methods for utilizing inter-microphone level differences to attenuate noise and enhance speech are provided. In exemplary embodiments, energy estimates of acoustic signals received by a primary microphone and a secondary microphone are determined in order to determine an inter-microphone level difference (ILD). This ILD in combination with a noise estimate based only on a primary microphone acoustic signal allow a filter estimate to be derived. In some embodiments, the derived filter estimate may be smoothed. The filter estimate is then applied to the acoustic signal from the primary microphone to generate a speech estimate.

Abstract: Systems and methods for utilizing inter-microphone level differences to attenuate noise and enhance speech are provided. In exemplary embodiments, energy estimates of acoustic signals received by a primary microphone and a secondary microphone are determined in order to determine an inter-microphone level difference (ILD). This ILD in combination with a noise estimate based only on a primary microphone acoustic signal allow a filter estimate to be derived. In some embodiments, the derived filter estimate may be smoothed. The filter estimate is then applied to the acoustic signal from the primary microphone to generate a speech estimate.

Abstract: Systems and methods for modification of an audio input signal are provided. In exemplary embodiments, an adaptive multiple-model optimizer is configured to generate at least one source model parameter for facilitating modification of an analyzed signal. The adaptive multiple-model optimizer comprises a segment grouping engine and a source grouping engine. The segment grouping engine is configured to group simultaneous feature segments to generate at least one segment model. The at least one segment model is used by the source grouping engine to generate at least one source model, which comprises the at least one source model parameter. Control signals for modification of the analyzed signal may then be generated based on the at least one source model parameter.

Abstract: Systems and methods for audio signal processing are provided. In exemplary embodiments, a filter cascade of complex-valued filters are used to decompose an input audio signal into a plurality of frequency components or sub-band signals. These sub-band signals may be processed for phase alignment, amplitude compensation, and time delay prior to summation of real portions of the sub-band signals to generate a reconstructed audio signal.

Abstract: Systems and methods for audio signal processing are provided. In exemplary embodiments, a filter cascade of complex-valued filters are used to decompose an input audio signal into a plurality of frequency components or sub-band signals. These sub-band signals may be processed for phase alignment, amplitude compensation, and time delay prior to summation of real portions of the sub-band signals to generate a reconstructed audio signal.

Abstract: The present technology measures distortion introduced by a noise suppression system. The distortion may be measured as the difference between a noise-reduced speech signal and an estimated idealized noise reduced reference (EINRR). The EINRR may be determined from a speech component and noise component that are pre-processed, and the EINRR may be used with masks associated with energies lost and added in the speech component and noise component. The EINRR may be calculated on a time varying basis.

Abstract: The present technology measures distortion introduced by a noise suppression system. The distortion may be measured as the difference between a noise-reduced speech signal and an estimated idealized noise reduced reference (EINRR). The EINRR may be determined from a speech component and noise component that are pre-processed, and the EINRR may be used with masks associated with energies lost and added in the speech component and noise component. The EINRR may be calculated on a time varying basis.

Abstract: The present technology measures distortion introduced by a noise suppression system. The distortion may be measured as the difference between a noise-reduced speech signal and an estimated idealized noise reduced reference (EINRR). The EINRR may be determined from a speech component and noise component that are pre-processed, and the EINRR may be used with masks associated with energies lost and added in the speech component and noise component. The EINRR may be calculated on a time varying basis.

Abstract: A method of removing reverberation from audio signals is disclosed. The method comprises spectro-temporally analyzing the first audio signal and the second audio signal to derive an energy function of time for a plurality of frequency bands. The method further comprises determining a delay stability between the energy function of time for the first audio signal and the second audio signal in each band, determining a gain function in each band based on the delay stability, adjusting the energy of the first audio signal and the second audio signal using the gain function within each band, and resynthesizing audio signals from the energy in each band of the first audio signal and the second audio signal.

Abstract: A system and method are disclosed for processing an audio signal including separating the audio signal into a plurality of streams which group sounds from a same source prior to classification and analyzing each separate stream to determine phoneme-level classification. One or more words of the audio signal may then be outputted.

Abstract: Systems and methods for audio signal processing are provided. In exemplary embodiments, a filter cascade of complex-valued filters are used to decompose an input audio signal into a plurality of frequency components or sub-band signals. These sub-band signals may be processed for phase alignment, amplitude compensation, and time delay prior to summation of real portions of the sub-band signals to generate a reconstructed audio signal.

Abstract: Systems and methods for modification of an audio input signal are provided. In exemplary embodiments, an adaptive multiple-model optimizer is configured to generate at least one source model parameter for facilitating modification of an analyzed signal. The adaptive multiple-model optimizer comprises a segment grouping engine and a source grouping engine. The segment grouping engine is configured to group simultaneous features segments to generate at least one segment model. The at least one segment model is used by the source grouping engine to generate at least one source model, which comprises the at least one source model parameter. Control signals for modification of the analyzed signal may then be generated based on the at least one source model parameter.