Google Inc.

Huawei Technologies Co., Limited

At&t Laboratories Cambridge Limited

University of Cambridge

Sick Ag

Simon J Godsill

Jan K Skoglund

Herbert Buchner

Karim Helwani

Milos Markovic

Bashar Ahmad

Jens Enzo Nyby Christensen

Christophe Andrieu

Alexander Frederick Goodyer

Provided are methods and systems for enhancing speech when corrupted by transient noise (e.g., keyboard typing noise). The methods and systems utilize a reference microphone input signal for the transient noise in a signal restoration process used for the voice part of the signal. A robust Bayesian statistical model is used to regress the voice microphone on the reference microphone, which allows for direct inference about the desired voice signal while marginalizing the unwanted power spectral values of the voice and transient noise. Also provided is a straightforward and efficient Expectation-maximization (EM) procedure for fast enhancement of the corrupted signal. The methods and systems are designed to operate easily in real-time on standard hardware, and have very low latency so that there is no irritating delay in speaker response.

Detection and suppression of keyboard transient noise in audio streams with aux keybed microphone

Detection and suppression of keyboard transient noise in audio streams with auxiliary keybed microphone

A signal processing apparatus and method are provided for separating a plurality of mixture signals from a MIMO system to iteratively obtain a plurality of output signals. The plurality of mixture signals are a response of the MIMO system to a plurality of source signals. The signal processing apparatus comprises a plurality of blind source separators including a first blind source separator based on a first blind source separation technique or algorithm and a second blind source separator based on a second blind source separation technique or algorithm, wherein the first blind source separator is configured to compute a first plurality of preliminary output signals on the basis of a first set of coefficients describing the MIMO system and wherein the second blind source separator is configured to compute a second plurality of preliminary output signals on the basis of a second set of coefficients describing the MIMO system.

Signal processing apparatus and method

Provided are methods and systems for acoustic keystroke transient cancellation/suppression for user communication devices using a semi-blind adaptive filter model. The methods and systems are designed to overcome existing problems in transient noise suppression by taking into account some less-defective signal as side information on the transients and also accounting for acoustic signal propagation, including the reverberation effects, using dynamic models. The methods and systems take advantage of a synchronous reference microphone embedded in the keyboard of the user device, and utilize an adaptive filtering approach exploiting the knowledge of this keybed microphone signal.

Acoustic keystroke transient canceler for speech communication terminals using a semi-blind adaptive filter model

Provided are methods and systems for detecting the presence of a transient noise event in an audio stream using primarily or exclusively the incoming audio data. Such an approach offers improved temporal resolution and is computationally efficient. The methods and systems presented utilize some time-frequency representation of an audio signal as the basis in a predictive model in an attempt to find outlying transient noise events and interpret the true detection state as a Hidden Markov Model (HMM) to model temporal and frequency cohesion common amongst transient noise events.

Keyboard typing detection and suppression

A method is provided of extracting desired signals st from contaminated signals yt measured via respective communication channels. The system comprising the desired signals st and the channels is modelled as a state space model. In the model, the desired signals have time-varying characteristics which vary more quickly than second time-varying characteristics of the channels.

Method for extracting a signal

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Cambridge, United Kingdom

Simon J Godsill