The present inventions, in one aspect, are directed to a portable activity monitoring device comprising a housing having a physical size and shape that is adapted to couple to the user's body, a plurality of sensors (for example, motion sensor and altitude sensor) disposed in the housing. The monitoring device may further include processing circuitry, disposed in the housing and electrically coupled to the plurality of sensor, to calculate the activity points corresponding to the physical activity of the user using the sensor data, wherein the activity points correlate to an amount and intensity of the physical activity of the user, and output the data which is representative of the activity points. The monitoring device may also include a display, coupled to the processing circuitry, may output the data which is representative of the activity points to the user.

Portable monitoring devices and methods of operating same

A method includes detecting a surface in proximity to a mobile device using sensor data and determining an acoustic reflectivity or acoustic absorptivity of the surface using the sensor data. The method may further compensate for the acoustic reflectivity or acoustic absorptivity by controlling a configurable group of microphones of the mobile device. Compensating for the surface acoustic reflectivity or acoustic absorptivity may include beamforming the outputs of the configurable group of microphones to obtain one of an omnidirectional beamform pattern or a directional beamform pattern. An apparatus that performs the method include a configurable group of microphones, a signal conditioner, and a surface compensator. The surface compensator is operative to detect a surface in proximity to the apparatus and determine a surface acoustic reflectivity or acoustic absorptivity.

Apparatus with Adaptive Audio Adjustment Based on Surface Proximity, Surface Type and Motion

A hybrid angular rate system is provided. In one aspect, the hybrid angular rate system at least includes two different types of angular rate sensors. The hybrid angular rate system may determine when to use the first angular rate sensor and when to use the second angular rate sensor to obtain angular rate measurements indicative of angular motion of the portable sensor device. Further, the hybrid angular rate system may determine one or more angular motion parameters describing angular motion of the portable sensor device using data from the first angular rate sensor, the second angular rate sensor, or the first angular rate sensor and the second angular rate sensor based on the determination.

Hybrid angular motion sensors

Systems and methods for multi-sourced noise suppression are provided. An example system may receive streams of audio data including a voice signal and noise, the voice signal including a spoken word. The streams of audio data are provided by distributed audio devices. The system can assign weights to the audio streams based at least partially on quality of the audio streams. The weights of audio streams can be determined based on signal-to-noise ratios (SNRs). The system may further process, based on the weights, the audio stream to generate cleaned speech. Each audio device comprises microphone(s) and can be associated with the Internet of Things (IoT), such that the audio devices are Internet of Things devices. The processing can include noise suppression and reduction and echo cancellation. The cleaned speech can be provided to a remote device for further processing which may include Automatic Speech Recognition (ASR).

Multi-Sourced Noise Suppression

A system comprising: an event server including a plurality of event agents for handling events occurring in a geographic space; a selector operable to select an event agent among the plurality of event agents for handling an event candidate based on a type of a source information; and a mobile object server including a mobile object agent assigned to a moving object in the geographic space, wherein the mobile object server is operable to execute the mobile object agent to collect information of an event from the selected event agent and provide the moving object with information that assists the moving object with traveling in the geographic space.

Management of events and moving objects

The disclosed system and method for a mobile device combines information derived from onboard sensors with conventional signal processing information derived from a speech or audio signal to assist in noise and echo cancellation. In some implementations, an Angle and Distance Processing (ADP) module is employed on a mobile device and configured to provide runtime angle and distance information to an adaptive beamformer for canceling noise signals, provides a means for building a table of filter coefficients for adaptive filters used in echo cancellation, provides faster and more accurate Automatic Gain Control (AGC), provides delay information for a classifier in a Voice Activity Detector (VAD), provides a means for automatic switching between a speakerphone and handset mode of the mobile device, or primary microphone and reference microphones and assists in separating echo path changes from double talk.

Sensor Fusion to Improve Speech/Audio Processing in a Mobile Device

This disclosure relates to adjusting a jitter buffer at a wireless device based on inter-arrival-jitter (IAJ). In one embodiment, an IAJ value may be calculated for each of multiple received packets. An IAJ distribution may be generated for the received packets. A target packet loss rate may be determined. A quality of service value for IAJ distributions corresponding to the target packet loss rate may be determined. A de-jitter delay value may be calculated based on the IAJ distribution and the quality of service value for IAJ distributions. The de-jitter delay value may be used to adjust the jitter buffer at the wireless device.

Adjusting a Jitter Buffer based on Inter Arrival Jitter

A jitter buffer in a Voice over LTE receiver may be influenced by radio level feedback (RLF) from both local and remote endpoints to preemptively adjust the jitter buffer delay in anticipation of predicted future losses that have a high probability of occurring. The radio events of the RLF and the scenarios that trigger the preemptive adjustments may be identified, and their use may be expressed in terms of mathematical formulas. Previously, the instantaneous jitter was derived from a weighted history of the media stream, and consequently only packets that had already been received were used to compute the instantaneous jitter to adjust the length of the buffer. By providing and using RLF from both local and remote endpoints, the anticipated delay—for packets that have not yet arrived—may be used to preemptively adjust the buffer, thereby minimizing packet loss without introducing unnecessary delay.

Tiange Shao

Papers

Sensor Fusion to Improve Speech/Audio Processing in a Mobile Device

Adjusting a Jitter Buffer based on Inter Arrival Jitter

Enhancing jitter buffer performance through radio level feedback