Nuance Communications, Inc.

Cerence Operating Company

Harman Becker Automotive Systems Gmbh

Harman International Industries, Inc.

Qnx Software Systems Limited

Markus Buck

Tim Haulick

Tobias Wolff

Gerhard Uwe Schmidt

Tobias Herbig

Timo Matheja

Meik Pfeffinger

Martin Roessler

Friedrich Faubel

Simon Graf

Günther Wirsching

Ingo Schalk-Schupp

Toby Christian Lawin-Ore

Julien Premont

Phillip Alan Hetherington

Mohamed Krini

Guido Kolano

Pierre Zakarauskas

Holger Quast

Christophe Ris

Naveen Kumar Desiraju

Michael Tropp

Walter Schnug

Jonas Jungclaussen

Klaus Linhard

Munir Nikolai Alexander Georges

Franz Gerl

Phil Hetherington

Samuel Ngouoko Mboungueng

Olga González Valbuena

Hans-Joerg Koepf

Lars König

Arthur Wolf

Josef Anastasiadis

Slawek Jarosz

Raymond Brückner

Bart D'hoore

Matthias Schulz

Stijn Verschaeren

Klaus Haindl

Oliver Van Porten

Stefan Hamerich

Rudi Vuerinckx

Olga Gonzalez Valbuena

Andreas Kirbach

Suhadi

Hakan Ari

Klaus Scheufele

Dieter Ranz

Ange Tchinda-Pockem

Martin Rössler

Julien Prémont

Emanuele Dalmasso

Andreas Kellner

Gaetan Martens

Amaury Astier

Suhadi Suhadi

Gunther Wirsching

Achim Eichentopf

Martin RÖßLER

Gerhard Schmidt

Samuel Kevin Ngouoko Mboungueng

Disclosed are systems, methods, and other implementations for acoustic interference suppression, including a method that includes obtaining a multi-source sound signal sample combining multiple sound components from a plurality of sound sources in a sound environment, with the plurality of sounds sources including one or more interfering sound sources produced by one or more loudspeakers in the sound environment, determining interfering sound characteristics for one or more sound signals that correspond to the one or more interfering sound sources, and suppressing at least one of the multiple sound components associated with the determined interfering sound characteristics for at least one of the one or more sound signals.

Acoustic interference suppression through speaker-aware processing

A vehicle includes a cabin, an internal-loudspeaker set an external-microphone set, and a signal processor that filters a raw audio signal that has been received by the external-microphone set broadcasts the resulting filtered audio signal into the cabin using the internal-loudspeaker set.

In-cabin audio filtering

An automotive assistant that is connected to microphones and loudspeakers that are associated with different seats in a passenger vehicle includes a dialog manager that is configured to initiate a dialog based on an utterance received at a first one of the microphones and to advance that dialog based on an utterance received from another of the microphones.

Speech dialog system for multiple passengers in a car

A vehicle defines an interior space and an exterior space. Within the vehicle are internal microphones that are disposed to capture an acoustic event that originated in an origination space, which is either the interior space or the exterior space. An infotainment system includes circuitry that forms a head unit having an acoustic-signal processor that is configured to receive, from the microphones, a sound vector indicative of the acoustic event and to identify the origination space based at least in part on the sound vector.

Determining whether an acoustic event originated inside or outside a vehicle

An In-Car Communication (ICC) system supports the communication paths within a car by receiving the speech signals of a speaking passenger and playing it back for one or more listening passengers. Signal processing tasks are split into a microphone related part and into a loudspeaker related part. A sound processing system suitable for use in a vehicle having multiple acoustic zones includes a plurality of microphone In-Car Communication (Mic-ICC) instances coupled and a plurality of loudspeaker In-Car Communication (Ls-ICC) instances. The system further includes a dynamic audio routing matrix with a controller and coupled to the Mic-ICC instances, a mixer coupled to the plurality of Mic-ICC instances and a distributor coupled to the Ls-ICC instances.

Communication system for multiple acoustic zones

An communication system supports communication paths within an environment by receiving speech signals of a speaker and playing it back for one or more listeners. Signal processing tasks are split into a microphone related part and into a loudspeaker related part. A sound processing system suitable for use in an environment having multiple acoustic zones includes a plurality of microphone communication instances coupled and a plurality of loudspeaker instances.

According to some aspects, a system for detecting a designated wake-up word is provided, the system comprising a plurality of microphones to detect acoustic information from a physical space having a plurality of acoustic zones, at least one processor configured to receive a first acoustic signal representing the acoustic information received by the plurality of microphones, process the first acoustic signal to identify content of the first acoustic signal originating from each of the plurality of acoustic zones, provide a plurality of second acoustic signals, each of the plurality of second acoustic signals substantially corresponding to the content identified as originating from a respective one of the plurality of acoustic zones, and performing automatic speech recognition on each of the plurality of second acoustic signals to determine whether the designated wake-up word was spoken.

Techniques for spatially selective wake-up word recognition and related systems and methods

There is provided a speech dialog system that includes a first microphone, a second microphone, a processor and a memory. The first microphone captures first audio from a first spatial zone, and produces a first audio signal. The second microphone captures second audio from a second spatial zone, and produces a second audio signal. The processor receives the first audio signal and the second audio signal, and the memory contains instructions that control the processor to perform operations of a speech enhancement module, an automatic speech recognition module, and a speech dialog module that performs a zone-dedicated speech dialog.

Multi-microphone speech dialog system for multiple spatial zones

A low-complexity method and apparatus for detection of voiced speech and pitch estimation is disclosed that is capable of dealing with special constraints given by applications where low latency is required, such as in-car communication (ICC) systems. An example embodiment employs very short frames that may capture only a single excitation impulse of voiced speech in an audio signal. A distance between multiple such impulses, corresponding to a pitch period, may be determined by evaluating phase differences between low-resolution spectra of the very short frames. An example embodiment may perform pitch estimation directly in a frequency domain based on the phase differences and reduce computational complexity by obviating transformation to a time domain to perform the pitch estimation. In an event the phase differences are determined to be substantially linear, an example embodiment enhances voice quality of the voiced speech by applying speech enhancement to the audio signal.

Low complexity detection of voiced speech and pitch estimation

A system and method for detecting multi-tone sirens despite environmental noises that may be present obtains a microphone input signal, applies, in real time, a time-frequency analysis to the microphone input signal to determine a time-frequency representation, provides at least one multi-tone model that has a plurality of tone duration patterns, performs multi-tone siren detection on the time-frequency representation, the detection based on the at least one multi-tone model and factoring of doppler shifts, and generates a detection result that can be used in systems for automated vehicles.

System and method for acoustic detection of emergency sirens

A system and method for generating a self-steering beamformer is provided. Embodiments may include receiving, at one or more microphones, a first audio signal and adapting one or more blocking filters based upon, at least in part, the first audio signal. Embodiments may also include generating, using the one or more blocking filters, one or more noise reference signals. Embodiments may further include providing the one or more noise reference signals to an adaptive interference canceller to reduce a beamformer output power level.

System and method for generating a self-steering beamformer

Gain mismatch and related problems can be solved by a system and method that applies an automatic microphone signal gain equalization without any direct absolute reference or calibration phase. The system and method performs the steps of receiving, by a computing device, a speech signal from a speaking person via a plurality of microphones, determining a speech signal component in the time-frequency domain for each microphone of the plurality of microphones, calculating an instantaneous cross-talk coupling matrix based on the speech signal components across the microphones, estimating gain factors based on calculated cross-talk couplings and a given expected cross-talk attenuation, limiting the gain factors to appropriate maximum and minimum values, and applying the gain factors to the speech signal used in the control path to control further speech enhancement algorithms or used in the signal path for direct influence on the speech enhanced audio output signal.

Multi-channel microphone signal gain equalization based on evaluation of cross talk components

A multi-mode voice controlled user interface is described. The user interface is adapted to conduct a speech dialog with one or more possible speakers and includes a broad listening mode which accepts speech inputs from the possible speakers without spatial filtering, and a selective listening mode which limits speech inputs to a specific speaker using spatial filtering. The user interface switches listening modes in response to one or more switching cues.

User dedicated automatic speech recognition

Systems and methods are introduced to perform noise suppression of an audio signal. The audio signal includes foreground speech components and background noise. The foreground speech components correspond to speech from a user's speaking into an audio receiving device. The background noise includes babble noise that includes speech from one or more interfering speakers. A soft speech detector determines, dynamically, a speech detection result indicating a likelihood of a presence of the foreground speech components in the audio signal. The speech detection result is employed to control, dynamically, an amount of attenuation of the noise suppression to reduce the babble noise in the audio signal. Further processing achieves a more stationary background and reduction of musical tones in the audio signal.

Babble noise suppression

Methods and apparatus for frequency selective signal mixing for speech enhancement. In one embodiment frequency-based channel selection is performed for signal magnitude, signal energy, and noise estimate using speaker activity detection information, signal-to-noise ratio, and/or signal level, Frequency-based channel selection is performed for a dynamic spectral floor to adjust the noise estimate using speaker dominance information. Noise reduction is performed on the signal for the selected channel.

Methods and apparatus for selective microphone signal combining

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Biberach, Germany

Markus Buck