Abstract:
Teachings herein prepare a digital image for display on a substantially transparent screen. The teachings advantageously recognize that the perceptibility of the digital image on the screen will often depend on what is visible to a user through the screen, since that will effectively serve as the background of the screen. A method of preparing a digital image thus includes dynamically calculating which part of an environmental background is visible to a user through the screen and thereby serves as an effective background of the screen. This calculation may entail obtaining an image of the environmental background and identifying which part of that image serves as the effective background (e.g., based on the angle at which the user views the screen). The method further includes composing the digital image for perceptibility as viewed against that effective background and outputting the composed image as digital data for display on the screen.
Abstract:
A common narrow-band speech signal is expanded into a wide-band speech signal. The expanded speech signal gives the impression of a wide-band speech signal regardless of what type of vocoder is used. Extending the narrow-band speech signal into a lower range involves analyzing the narrow-band speech signal to generate one or more parameters, and synthersizing a lower frequency-band signal based on at least one of the one or more parameters. The synthesized lower frequency-band signal is then combined with a signal that is derived from (e.g., via up-sampling) the narrow-band speech signal. In preferred emobodiments, a pitch frequency parameter is generated, and generation of the lower frequency-band signal includes generating continuous sine tones that are frequency shifted with the pitch frequency parameter.
Abstract:
A data-processing unit has a fetching circuitry (20) and execution circuitry (30a, 30b). The data-processing unit has an instruction set comprising a nested-loop instruction. The fetching circuitry is arranged to fetch the nested-loop instruction, and the execution circuitry is arranged to execute the nested-loop instruction. The nested-loop instruction comprises at least one instruction field that is adapted to indicate a number of iterations of an outer loop of the nested loop and one or more operations to be performed by the outer loop. Moreover, the at least one instruction field is further adapted to indicate a number of iterations of an inner loop of the nested loop and one or more operations to be performed by the inner loop. A method for fetching, decoding, and executing the nested-loop instruction is also described as well as the structure of the nested-loop instruction.
Abstract:
Methods and apparatus for providing speech enhancement in noise reduction systems include spectral subtraction algorithms using linear convolution, causal filtering and/or spectrum dependent exponential averaging of the spectral subtraction gain function. According to exemplary embodiments, low order spectrum estimates are developed which have less frequency resolution and reduced variance as compared to spectrum estimates in conventional spectral subtraction systems. The low order spectra are used to form a gain function having a desired low variance which in turn reduces musical tones in the spectral subtraction output signal. Advantageously, the gain function can be further smoothed across blocks using input spectrum dependent exponential averaging. Additionally, the low order of the gain function permits a phase to be added during interpolation so that the spectral subtraction gain filter is causal and prevents discontinuities between blocks.
Abstract:
Methods and apparatus for providing speech enhancement in noise reduction systems include spectral subtraction algorithms using linear convolution, causal filtering and/or spectrum dependent exponential averaging of the spectral subtraction gain function. According to exemplary embodiments, low order spectrum estimates are developed which have less frequency resolution and reduced variance as compared to spectrum estimates in conventional spectral subtraction systems. The low order spectra are used to form a gain function having a desired low variance which in turn reduces musical tones in the spectral subtraction output signal. Advantageously, the gain function can be further smoothed across blocks using input spectrum dependent exponential averaging. Additionally, the low order of the gain function permits a phase to be added during interpolation so that the spectral subtraction gain filter is causal and prevents discontinuities between blocks.
Abstract:
A common narrow-band speech signal is expanded into a wide-band speech signal. The expanded speech signal gives the impression of a wide-band speech signal regardless of what type of vocoder is used. Extending the narrow-band speech signal into a lower range involves analyzing the narrow-band speech signal to generate one or more parameters, and synthesizing a lower frequency-band signal based on at least one of the one or more parameters. The synthesized lower frequency-band signal is then combined with a signal that is derived from (e.g., via up-sampling) the narrow-band speech signal. In preferred embodiments, a pitch frequency parameter is generated, and generation of the lower frequency-band signal includes generating continuous sine tones that are frequency shifted with the pitch frequency parameter.
Abstract:
Methods and apparatus for providing speech enhancement in noise reduction systems include spectral subtraction algorithms using linear convolution, causal filtering and/or spectrum dependent exponential averaging of the spectral subtraction gain function. According to exemplary embodiments, successive blocks of a spectral subtraction gain function are averaged based on a discrepancy between an estimate of a spectral density of a noisy speech signal and an averaged estimate of a spectral density of a noise component of the noisy speech signal. The successive gain function blocks are averaged, for example, using controlled exponential averaging. Control is provided, for example, by making a memory of the exponential averaging inversely proportional to the discrepancy. Alternatively, the averaging memory can be made to increase in direct proportion with decreases in the discrepancy, while exponentially decaying with increases in the discrepancy to prevent audible voice shadows.
Abstract:
Techniques for enhancing performance in Industrial Internet-of-Things (IIoT) scenarios, including techniques for time-sensitive networking (TSN) and 5G wireless network integration. An example method, performed by a wireless device, comprises receiving system information (SI) from a radio base station (RBS) of a radio access network (RAN), the SI being indicative of support for TSN through the RBS, and establishing at least one TSN stream with an external data network, through the RBS. The example method further includes receiving a first timing signal from the wireless communications network, via the RBS, receiving a second timing signal from the external TSN data network to which the wireless device is connected, comparing the first timing signal to the second timing signal to determine an offset, and transmitting the offset to the wireless communications network.