Telefonaktiebolaget Lm Ericsson (Publ)

Staffansboda Compagnie Ab

Limes Audio Ab

Ingvar Claesson

Sven Nordholm

Harald Gustafsson

Thomas Lago

Lars Hakansson

Andreas Nilsson

Jim Rasmusson

Ulf Axel Lindgren

Christian Schüldt

Fredric Lindström

Pėr Ljungberg

Johan Udén

Peter Lakatos

Per Rosengren

Mattias Dahl

The present invention relates to a device, such as a communication device, comprising an adaptive foreground filter configured to calculate a first echo estimation signal based on a first input signal, and an adaptive background filter being more rapidly adapting than the foreground filter and configured to calculate a second echo estimation signal based on said first input signal. Embodiments of the device further comprise damping control means for controlling damping of an echo-cancelled output signal. The device in various embodiments includes that the damping control means is configured to calculate a maximum echo estimation signal using both the first and the second echo estimation signals, and control the damping of the echo-cancelled output signal based on said maximum echo estimation signal and/or a signal derived from said maximum echo estimation signal.

Device and method for controlling damping of residual echo

A device and method for vibration control in a machine for cutting, said machine comprising a cutting tool supported by a tool holder. The device comprises a control unit and converting means which are connectible to the control unit and comprise a vibration sensor and an actuator. The actuator comprises an active element which converts an A.C. voltage supplied by the control unit to the actuator into dimensional changes. Said active element is adapted to be embedded in the body of the tool holder and in such manner that said dimensional changes impart bending to the body of the tool holder.

Method and device for vibration control

A device increases the surface smoothness of a turned surface. The device comprising a control system with a control unit and an actuator connectible to the control unit and connectible with a tool holder. The actuator in adapted to impart a vibrating motion in the lateral direction to the tool holder. A method will also increase the surface smoothness of a turned surface, comprising the step of controlling the vibrations of the tool holder during turning. The method also comprises the step of imparting a vibrating motion in the lateral direction to the tool holder. Moreover, a turning lathe and a turning tool holder which like the device are designed to generate vibrating motion in the lateral direction.

Method and device for controlling a turning operation

A system and method for suppressing disturbance signal components in a communication signal is disclosed. The system and method utilize a priori information about the fundamental frequency of the disturbance signal component to generate an estimate of the disturbance signal component. This estimated disturbance signal may be subtracted from the communication signal to suppress the disturbance signal component in the communication signal.

System and method for noise suppression in a communication signal

Speech enhancement is provided in dual microphone noise reduction systems by including spectral subtraction algorithms using linear convolution, causal filtering and/or spectrum dependent exponential averaging of the spectral subtraction gain function. According to exemplary embodiments, when a far-mouth microphone is used in conjunction with a near-mouth microphone, it is possible to handle non-stationary background noise as long as the noise spectrum can continuously be estimated from a single block of input samples. The far-mouth microphone, in addition to picking up the background noise, also picks up the speaker's voice, albeit at a lower level than the near-mouth microphone. To enhance the noise estimate, a spectral subtraction stage is used to suppress the speech in the far-mouth microphone signal. To be able to enhance the noise estimate, a rough speech estimate is formed with another spectral subtraction stage from the near-mouth signal. Finally, a third spectral subtraction function is used to enhance the near-mouth signal by suppressing the background noise using the enhanced background noise estimate. A controller dynamically determines any or all of a first, second, and third subtraction factor for each of the first, second, and third spectral subtraction stages, respectively.

System and method for dual microphone signal noise reduction using spectral subtraction

A beamformer is calibrated for use as an acoustic echo canceler in a hands-free communications environment having a loudspeaker and a plurality of microphones. To perform the calibration, a number of adaptive filters are provided in correspondence with each of the microphones, and each of the adaptive filters is trained to model echo properties of the environment as experienced by the corresponding one of the microphones. A target source is activated, thereby generating an acoustic signal that is received by the microphones. The trained adaptive filters are then used to generate jammer signals by, for example, having each one filter a pseudo noise signal. Respective ones of the jammer signals are then combined with corresponding signals supplied by the microphones, thereby generating combination signals. The combination signals are then used to adapt the beamformer to cancel the jammer signals. In another aspect of the invention, the adaptive filters may be utilized during normal operation by having them perform an echo cancellation operation on each of the signals that is to be supplied to the calibrated beamformer.

Generating calibration signals for an adaptive beamformer

Speech enhancement is provided in dual microphone noise reduction systems by including spectral subtraction algorithms using linear convolution, causal filtering and/or spectrum dependent exponential averaging of the spectral subtraction gain function. According to exemplary embodiments, when a far-mouth microphone is used in conjunction with a near-mouth microphone, it is possible to handle non-stationary background noise as long as the noise spectrum can continuously be estimated from a single block of input samples. The far-mouth microphone, in addition to picking up the background noise, also picks up the speaker's voice, albeit at a lower level than the near-mouth microphone. To enhance the noise estimate, a spectral subtraction stage is used to suppress the speech in the far-mouth microphone signal. To be able to enhance the noise estimate, a rough speech estimate is formed with another spectral subtraction stage from the near-mouth signal. Finally, a third spectral subtraction function is used to enhance the near-mouth signal by suppressing the background noise using the enhanced background noise estimate.

For purposes of noise suppression, spectral subtraction filtering is performed in sample-wise fashion in the time domain using a time-domain representation of a spectral subtraction gain function computed in block-wise fashion in the frequency domain. By continuously performing time-domain filtering on a sample by sample basis, the disclosed methods and apparatus avoid block-processing delays associated with frequency-domain based spectral subtraction systems. Consequently, the disclosed methods and apparatus are particularly well suited for applications requiring very short processing delays. Moreover, since the spectral subtraction gain function is computed in a block-wise fashion in the frequency domain, high quality performance in terms of reduced tonal artifacts and low signal distortion is retained.

Signal noise reduction by time-domain spectral subtraction

For purposes of noise suppression, spectral subtraction filtering is performed in sample-wise fashion in the time domain using a time-domain representation of a spectral subtraction gain function computed in block-wise fashion in the frequency domain. By continuously performing time-domain filtering on a sample by sample basis, the disclosed methods and apparatus avoid block-processing delays associated with frequency-domain based spectral subtraction systems. Consequently, the disclosed methods and apparatus are particularly well suited for applications requiring very short processing delays. In applications where only stationary, low-energy background noise is present, computational complexity is reduced by generating a number of separate spectral subtraction gain functions during an initialization period, each gain function being suitable for one of several predefined classes of input signal (e.g., for one of several predetermined signal energy ranges), and thereafter fixing the several gain functions until the input signal characteristics change.

Signal noise reduction by time-domain spectral subtraction using fixed filters

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.

Signal noise reduction by spectral subtraction using spectrum dependent exponential gain function averaging

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.

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Dalby, Sweden

Ingvar Claesson