Harman International Industries, Inc.

Rajesh Biswal

Pratyush Sahay

Debashis Mukherjee

Pranjal Chakraborty

Arindam Dasgupta

Srinivas Sai

Aashish Kumar

Srinivas Kruthiventi Subrahmanyeswara Sai

George Jose

Jigar Mistry

The current disclosure relates to systems and methods for wakeword or keyword detection in Virtual Personal Assistants (VPAs). In particular, systems and methods are provided for wakeword detection using deep neural networks including a parametric pooling layer, wherein the parametric pooling layer includes trainable parameters, enabling the layer to learn to distinguish between informative feature vectors and non-informative/noisy feature vectors extracted from a variable length acoustic signal. In one example, a parametric pooling layer may aggregate a variable length feature map, comprising a plurality of feature vectors extracted from an acoustic signal, into an embedding vector of pre-determined length, by weighting each of the plurality of feature vectors based on one or more learned parameters in a parametric pooling layer, and aggregating the plurality of weighted feature vectors into the embedding vector.

System and method for robust wakeword detection in presence of noise in new unseen environments without additional data

A system for controlling a vehicle includes a microphone, at least one vehicle component, and an interface system communicatively coupled to the microphone and the at least one vehicle component, the interface system configured to detect, via the microphone, an utterance of a vocal command by an occupant of the vehicle, transmit the utterance to at least one of a virtual personal assistant (VPA) of the vehicle and a VPA of a mobile device positioned within the vehicle, receive control signals from at least one of the VPA of the vehicle and the VPA of the mobile device, the control signals generated according to the vocal command, and transmit the control signals to the at least one vehicle component for controlling the at least one vehicle component.

Voice control of vehicle systems

A voice command application allows a user to configure an infotainment system to respond to customized voice commands. The voice command application exposes a library of functions to the user which the infotainment system can execute via interaction with the vehicle. The voice command application receives a selection of one or more functions and then receives a speech sample of the voice command. The voice command application generates sample metadata that includes linguistic elements of the voice command, and then generates a command specification. The command specification indicates the selected functions and the sample metadata for storage in a database. Subsequently, the voice command application receives the voice command from the user and locates the associated command specification in the database. The voice command application then extracts the associated set of functions and causes the vehicle to execute those functions to perform vehicle operations.

Configurable speech interface for vehicle infotainment systems

The present disclosure relates to systems, devices and methods for image presentation for vehicle driver assistance. In one embodiment, a method includes receiving image data representing an outside of a vehicle and enhancing the image data. Image enhancement can include inverting the image data, running a dehazing operation based on scene radiance, medium transmission and atmospheric light of the image data. The method may also include generating reconstructed image data from the enhanced image data by performing a sparse representation of the enhanced image data for denoising of the enhanced image data, and performing a learning operation to identify and enhance objects of interest in the enhanced image data with the sparse representation. The method also includes outputting the reconstructed image data to a display unit of the vehicle. Vehicle driver assist systems and devices are provided to enhance image data detected by vehicle cameras and wearable devices.

System and method for image presentation by a vehicle driver assist module

The present disclosure relates to systems, devices and methods for vehicle headlight control. In one embodiment, a method includes receiving image data from a front facing camera of the vehicle and detecting at least one object in the image data. An illumination level of the at least one object in the image data is detected and a control setting is determined to modify illumination of at least one lighting element of the vehicle, wherein the control setting is determined to increase an illumination level for the at least one object. The method also includes controlling the at least one lighting element of the vehicle in response to the control setting. Vehicle systems and devices are provided with a front facing camera and a control unit for a plurality of lighting elements wherein control settings may be modified based on objects detected in image data.

System and method for vehicle headlight control

In one embodiment of the present invention, a wait time client enables prediction of wait times (e.g., time required to checkout at a grocery store) based on crowdsourced wait data. In operation, the wait time application downloads predicted wait data from a server. The predicted wait data reflects measured wait times for one or more location, such as the ticket line at a movie theater. The wait time client then selects a wait time data point that corresponds to a location of a point-of-interest. Based on the selected wait time data point, the wait time client determines a predicted wait time at the point-of-interest. Advantageously, by leveraging crowdsourced, deterministically measured wait times, the wait time clients enables the incorporation of realistic and up-to-date predicted wait times into the trip planning process.

Approaches to crowdsourced-based wait time estimates

Embodiments are disclosed for systems and methods for controlling operation of an in-vehicle computing system. In some embodiments, an in-vehicle computing system includes a processor, an external device interface communicatively coupleable to an extra-vehicle server, and a storage device storing instructions executable by the processor to receive information from a navigation subsystem and one or more sensors of the vehicle. The information may include user information identifying one or more occupants of the vehicle with one or more accounts of a social media network. The instructions may also be executable to send the received information to the server, receive instructions from the server, and transmit control instructions to one or more vehicle systems based on the identified action. The instructions may identify an action to be performed based on the received information.

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Bengaluru, India

Rajesh Biswal