Accusonus, Inc.

Meta Platforms Technologies, LLC

Accusonus S.a.

Alexandros Tsilfidis

Elias Kokkinis

Michael A Tzannes

A method for mixing, processing and enhancing signals using signal decomposition is presented. A method for improving sorting of decomposed signal parts using cross-component similarity is also provided.

Methods and systems for processing and mixing signals using signal decomposition

A method for improving decomposition of digital signals using training sequences is presented. A method for improving decomposition of digital signals using initialization is also provided. A method for sorting digital signals using frames based upon energy content in the frame is further presented. A method for utilizing user input for combining parts of a decomposed signal is also presented.

Methods and systems for improved signal decomposition

A method of decomposing digital signals using non-negative matrix factorization by generating an initial set of values in a row in the weight matrix from a ratio of a first function of a first signal of a plurality of digital signals divided by a second function of at least two other signals of the plurality of the digital signals, wherein the row in the weight matrix determines a decomposition of the plurality of digital signals into signal components.

Weight matrix initialization method to improve signal decomposition

A method is presented for estimating and suppressing reverberation from a digital reverberant signal. A method for changing a first reverberation estimation according to another reverberation estimation is further provided. A method for controlling the reverberation suppression rate is also presented.

Single-channel, binaural and multi-channel dereverberation

A system and method for constructing training dictionaries with multichannel information. An exemplary method takes into account the effect of the acoustic path while training multichannel acoustic data. A method that uses different time-frequency resolutions in machine learning training is also presented.

Data training in multi-sensor setups

A system and method of decomposing a source signal comprising first and second sound signals, using an extended time-frequency transformation formed by combining a time frequency transformation of a first representation of the source signal with a time-frequency transformation of a second representation of the source signal. The source signal can comprise music, speech, video or other multimedia signals and the decomposition can be controlled by a single knob user interface.

Method and system of signal decomposition using extended time-frequency transformations

Method and system for use with multimedia signals that analyzes the signals into time-frequency frames over first and second time periods. Estimates of the noise and/or reverberation are derived from the frames. Gains are derived from the estimates and raised to a power to create modified gains. The modified gains are applied to the frame in the appropriate time periods. Modified multimedia signals are output after being processed by the modified gains.

Method and system for denoise and dereverberation in multimedia systems

A method for wireless data exchange between devices in live events is presented. A method for exploring data of multiple devices in order to get information on the acoustic paths in different locations of venues is also provided. A method of exploring the microphones of sound-capturing devices of live event's audience is also presented.

Wireless exchange of data between devices in live events

Method and system for use with audible signals that analyzes the signals into time-frequency frames over first and second time periods. Estimates of the noise and/or reverberation are derived from the frames. Gains are derived from the estimates and raised to a power to create modified gains. The modified gains are applied to the frames in the appropriate time periods. Modified audible signals are output after being processed by the modified gains.

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Athens, Greece

Alexandros Tsilfidis