公开(公告)号：WO2018119470A1

公开(公告)日：2018-06-28

申请号：PCT/US2017/068362

申请日：2017-12-22

Applicant: SYNAPTICS INCORPORATED

Inventor： KASKARI, Saeed Mosayyebpour ,  NESTA, Francesco ,  THORMUNDSSON, Trausti

IPC: H04R5/04 ,  H04R3/04

Abstract: Systems and methods for processing multichannel audio signals include receiving a multichannel time-domain audio input, transforming the input signal to plurality of multi-channel frequency domain, k-spaced under-sampled subband signals, buffering and delaying each channel, saving a subset of spectral frames for prediction filter estimation at each of the spectral frames, estimating a variance of the frequency domain signal at each of the spectral frames, adaptively estimating the prediction filter in an online manner using a recursive least squares (RLS) algorithm, linearly filtering each channel using the estimated prediction filter, nonlinearly filtering the linearly filtered output signal to reduce residual reverberation and the estimated variances, producing a nonlinearly filtered output signal, and synthesizing the nonlinearly filtered output signal to reconstruct a dereverberated time-domain multi-channel audio signal.

公开(公告)号：WO2019113130A1

公开(公告)日：2019-06-13

申请号：PCT/US2018/063937

申请日：2018-12-04

Applicant: SYNAPTICS INCORPORATED

Inventor： KASKARI, Saeed Mosayyebpour ,  NESTA, Francesco

IPC: G10L25/78 ,  G10L19/02 ,  G10L25/18

Abstract: An audio processing device or method includes an audio transducer operable to receive audio input and generate an audio signal based on the audio input. The audio processing device or method also includes an audio signal processor operable to extract local features from the audio signal, such as Power-Normalized Coefficients (PNCC) of the audio signal. The audio signal processor also is operable to extract global features from the audio signal, such as chroma features and harmonicity features. A neural network is provided to determine a probability that a target audio is present in the audio signal based on the local and global features. In particular, the neural network is trained to output a value indicating whether the target audio is present and locally dominant in the audio signal.

公开(公告)号：WO2018119467A1

公开(公告)日：2018-06-28

申请号：PCT/US2017/068358

申请日：2017-12-22

Applicant: SYNAPTICS INCORPORATED

Inventor： KASKARI, Saeed Mosayyebpour ,  NESTA, Francesco

IPC: G10L19/008 ,  G10L21/0208

CPC classification number: G10L21/0264 ,  G10L19/008 ,  G10L21/0216 ,  G10L25/78 ,  G10L2021/02082 ,  G10L2021/02166 ,  H04R3/005

Abstract: Audio signal processing for adaptive de-reverberation uses a least mean squares (LMS) filter that has improved convergence over conventional LMS filters, making embodiments practical for reducing the effects of reverberation for use in many portable and embedded devices, such as smartphones, tablets, laptops, and hearing aids, for applications such as speech recognition and audio communication in general. The LMS filter employs a frequency-dependent adaptive step size to speed up the convergence of the predictive filter process, requiring fewer computational steps compared to a conventional LMS filter applied to the same inputs. The improved convergence is achieved at low memory consumption cost. Controlling the updates of the prediction filter in a high non-stationary condition of the acoustic channel improves the performance under such conditions. The techniques are suitable for single or multiple channels and are applicable to microphone array processing.