Ford Global Technolgoies, LLC

Leah N Busch

Ranjani Rangarajan

Joshua R Wheeler

Scott Andrew Amman

John Edward Huber

Erick Michael Lavoie

Nikhitha Bekkanti

Andrea Bowes Chowanic

Jake S Schwartz

Marla Johnston

An Ji

David Graham Smith

Thomas Chrapkiewicz

Jessamyn Smallenburg

Karthik Krishnamurthy

The disclosure generally pertains to systems and methods for identifying a location of an occupant in a vehicle. In an example method, a processor deconvolves a vocal utterance by an occupant of a vehicle and also determines an angle of arrival of the vocal utterance. The location of the occupant in the vehicle is then identified by the processor based on evaluating the deconvolved vocal utterance and the angle of arrival of the vocal utterance. Deconvolving the vocal utterance can involve applying a cabin impulse response to the vocal utterance for eliminating undesirable effects that may be imposed upon the vocal utterance by acoustic characteristics of the cabin of the vehicle (echo, sound reflections, sound damping, reverberation etc.). In some applications, the processor may refer to a lookup table to estimate a location of the occupant in the vehicle.

System and method to identify a location of an occupant in a vehicle

A system for dynamically controlling an echo canceler includes a processor programmed to receive audio data from an audio sensor, to determine a present type of noise in the received audio data, based on the present type of noise, to determine a number of taps to be removed from an echo canceler, and to execute the echo canceler with a reduced number of taps based on the number of taps to be removed.

Echo cancelation

The disclosure describes systems and methods for processing audio signals in a vehicle to perform sound source separation. The sound source separation is performed using transfer functions and involves separation of the speech of multiple occupants. The separated speech can be used to isolate and correctly respond to a command to control vehicle systems.

Systems and methods for audio processing

Detecting and isolating competing speech for voice controlled systems are provided herein. An example method includes isolating a voice command from a plurality of competing voice sound signals received internally or externally to a vehicle, wherein at least a portion of the plurality of competing voice sound signals are received using a sensor coupled with a window of the vehicle, and processing the voice command by the voice command system.

Detecting and isolating competing speech for voice controlled systems

Method and apparatus are disclosed for accelerometer-based external sound monitoring for voice controlled autonomous parking. An example vehicle includes a body control module, an infotainment head unit, and an autonomy unit. The example body control module communicatively couples to a mobile device. The example infotainment head unit communicatively couples to an accelerometer mounted on a window of the vehicle. The example autonomy unit autonomously parks the vehicle in response to a first key word detected by the accelerometer when (i) a button is activated on the infotainment head unit and (ii) a message from the mobile device is being periodically received.

Accelerometer-based external sound monitoring for voice controlled autonomous parking

Method and apparatus are disclosed for monitoring of vehicle window vibrations for voice-command recognition. An example vehicle includes a window, an outer layer, a vibration sensor coupled to the window to detect audio vibrations, an audio actuator coupled to the outer layer to vibrate the outer layer, and a controller. The controller is to detect a voice command from a user via the vibration sensor, identify an audio response based upon the voice command, and emit the audio response to the user via the audio actuator.

Monitoring of vehicle window vibrations for voice-command recognition

Method and apparatus are disclosed for speech recognition for vehicle voice commands. An example vehicle includes a microphone to collect a signal including a voice command, memory, and a controller. The controller is configured to determine an initial identification by feeding the signal into a first automatic speech recognition (ASR) engine and determine habits by feeding user history into a habits engine. The controller also is configured to identify the voice command by feeding the signal, the initial identification, and the habits into a second ASR engine. The controller also is configured to perform a vehicle function based on the voice command.

Speech recognition for vehicle voice commands

Exemplary embodiments described in this disclosure are generally directed to systems and methods for predicting a behavior of a pedestrian on the basis of a behavioral profile of the pedestrian. The behavioral profile may be generated in a personal communication device of the pedestrian (such as a smartphone) based on activities performed by the pedestrian such as walking on a sidewalk, stepping off the sidewalk to walk on a road, standing on a sidewalk waiting for a traffic light to change, stepping onto the road when waiting for a traffic light to change, and/or crossing a road when the traffic light is red. The behavioral profile may also be based on other factors such as a traffic citation, an accident report, a status of a driver's license, and/or physical characteristics of the pedestrian (age, gender, etc.).

Systems and methods for predicting pedestrian behavior

Method and apparatus are disclosed for accelerometer-based external sound monitoring for position aware autonomous parking. An example vehicle includes accelerometers mounted on windows of the vehicle, a computing platform communicatively coupled to the accelerometers, and an autonomy unit. The computing platform receives, via the accelerometers, signals indicative of a stop command associated with a voice. Additionally, the computing platform validates the stop command when the voice either is authorized or originates from within an emergency zone. The autonomy unit prevents autonomous motion of the vehicle in response to receiving the validated stop command.

Accelerometer-based external sound monitoring for position aware autonomous parking

Method and apparatus are disclosed for accelerometer-based external sound monitoring during low speed maneuvers. An example vehicle includes accelerometers affixed to windows of the vehicle, speakers located inside the vehicle, and an infotainment head unit. Each of the speakers is uniquely associated with one of the accelerometers. The infotainment head unit, when a speed of the vehicle satisfies a threshold, selects a zone corresponding to a direction of travel of the vehicle. Additionally, the infotainment head unit plays signals captured by the accelerometers associated with the selected zone on the corresponding speakers.

Accelerometer-based external sound monitoring during low speed maneuvers

Method and apparatus are disclosed for determining and accounting for distortions to an audio signal due to the geometric properties of the interior cabin of a vehicle. An example vehicle includes a microphone, a seat having a plurality of seat positions, and a processor. The processor is configured to determine a first seat position corresponding to a point in time at which an audio signal is received, determine a cabin impulse response corresponding to the first seat position, and determine a filtered audio signal based on the cabin impulse response and the audio signal.

Systems and methods for removing vehicle geometry noise in hands-free audio

Voice control is extended outside of an automotive vehicle by an access system associated with a door and window. An accelerometer is mounted on the window to generate a vibration signal. A passive entry system generates an unlock standby signal when an authorized user carrying a wireless fob is detected proximate the door. A voice recognizer in the vehicle is activated by the standby signal to scan the vibration signal for a spoken command for opening the door. A door actuator is activated by the voice recognizer when the command is detected.

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Dearborn, MI, United States of America

Leah N Busch