Abstract:
Method and devices for processing audio signals based on sound profiles are provided. A reproduction device can request a sound profile based on user information, device information, media metadata or a combination. The sound profiles can be customized and shared across multiple devices. User interfaces allow for the input of information that allows the reproduction device or a server in the cloud to select, modify, store, and analyze sound profiles. Deeper analysis allows for the improvement of sound profiles for individuals and groups. Intensity scoring of a music library can also be conducted.
Abstract:
Devices, systems and processes for an integrated internal and external camera system that enhances the passenger experience in vehicles are described. One example method for enhancing a passenger experiences includes capturing a first set of images of an area around the vehicle using an external camera system, capturing a second set of images of one or more passengers inside the vehicle using an internal camera system, recognizing at least one gesture made by the one or more passengers based on the second set of images, identifying an object or a location external to the vehicle based on the first set of images and the at least one gesture, and displaying information related to the object or the location to the one or more passengers.
Abstract:
Devices, systems and processes for a dynamic microphone system that enhances the passenger experience in autonomous vehicles are described. One example method for enhancing a passenger experiences includes generating, using an artificial intelligence algorithm, a plurality of filters based on a plurality of stored waveforms previously recorded by each of one or more passengers and a plurality of recordings of one or more noise sources, capturing voice commands from at least one of the one or more passengers inside the autonomous vehicle, generating voice commands with reduced distortion based on processing the voice commands using the plurality of filters, and instructing, based on the voice commands with reduced distortion, the autonomous vehicle to perform one or more actions.
Abstract:
Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate first sensor data and second sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the first sensor data. The system may also include a second computing device configured to determine a state of the resource-constrained environment based on input of the second sensor data to the neural network structure. The system may also include a controller located in the resource-constrained environment configured to control a device in the resource-constrained environment based on the state of the resource-constrained environment determined by the second computing device. The second computing device may be further configured to calculate an activation area for the neural network structure.
Abstract:
Devices, systems and processes for the detection of unsafe cabin conditions that provides a safer passenger experience in autonomous vehicles are described. One example method for enhancing passenger safety includes capturing at least a set of images of one or more passengers in the vehicle, determining, based on the set of images, the occurrence of an unsafe activity in an interior of the vehicle, performing, using a neural network, a classification of the unsafe activity, and performing, based on the classification, one or more responsive actions.
Abstract:
Method and devices for processing audio signals based on sound profiles are provided. A sound profile can include data related to haptic movement of the audio data which is specific to a left ear or a right ear, demographic information, ethnicity information, age information, location information, social media information, intensity score of the audio data, previous usage information, or device information. A sound profile can be customized for individual user to include the inaudible frequency range at high frequency end and low frequency end. Audio data within the inaudible frequency range can be compensated by haptic movement corresponding to the inaudible frequency range. A sound profile can further include an audio frequency range and its lowest audible volume for a user. A sound profile can be provided to a user without any action from the user's part.
Abstract:
Devices, systems and processes for a dynamic microphone system that enhances the passenger experience in autonomous vehicles are described. One example method for enhancing a passenger experiences includes generating, using an artificial intelligence algorithm, a plurality of filters based on a plurality of stored waveforms previously recorded by each of one or more passengers and a plurality of recordings of one or more noise sources, capturing voice commands from at least one of the one or more passengers inside the autonomous vehicle, generating voice commands with reduced distortion based on processing the voice commands using the plurality of filters, and instructing, based on the voice commands with reduced distortion, the autonomous vehicle to perform one or more actions.
Abstract:
Method and devices for testing a headphone with increased sensation are provided. The headphone can filter and amplify low frequency audio signals, which are then sent to a haptic device in the headphone. The haptic device can cause bass sensations at the top of the skull and at both ear cups. The testing system can evaluate the haptic and acoustic sensations produced by the headphone to evaluate if they have been properly assembled and calibrate the headphones if necessary.
Abstract:
Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate first sensor data and second sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the first sensor data. The system may also include a second computing device configured to determine a state of the resource-constrained environment based on input of the second sensor data to the neural network structure. The system may also include a controller located in the resource-constrained environment configured to control a device in the resource-constrained environment based on the state of the resource-constrained environment determined by the second computing device. The second computing device may be further configured to calculate an activation area for the neural network structure.
Abstract:
Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate first sensor data and second sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the first sensor data. The system may also include a second computing device configured to determine a state of the resource-constrained environment based on input of the second sensor data to the neural network structure. The system may also include a controller located in the resource-constrained environment configured to control a device in the resource-constrained environment based on the state of the resource-constrained environment determined by the second computing device. The second computing device may be further configured to calculate an activation area for the neural network structure.