Abstract: The present invention discloses a multilayer system utilizing a trusted execution environment for creating isolated environments to implement an operating system for commercial drones with increased security. The trusted execution environment creates an isolated environment that runs parallel with the operating system. The utilization of the trusted execution environment as the three-layer system is segmented into three subsystems, wherein each subsystem provides a separate functionality and helps in controlling the flight of the drone.

Abstract: The present application relates to the field of battery technologies, for example, to a battery, a battery module, and a battery pack. The battery includes a housing, a terminal pole column, and an upper plastic member. A first through hole is defined on a top cover of the housing. The terminal pole column passes through the first through hole. The upper plastic member is disposed above the top cover of the housing. The terminal pole column is capable of passing through the upper plastic member and bending outward to form a flange, and the terminal pole column abuts against the upper plastic member, and an upper top surface of the terminal pole column and an upper top surface of the upper plastic member are flush with each other.

Abstract: A device performs a method for using image data to aid voice recognition. The method includes the device capturing image data of a vicinity of the device and adjusting, based on the image data, a set of parameters for voice recognition performed by the device. The set of parameters for the device performing voice recognition include, but are not limited to: a trigger threshold of a trigger for voice recognition; a set of beamforming parameters; a database for voice recognition; and/or an algorithm for voice recognition. The algorithm may include using noise suppression or using acoustic beamforming.

Abstract: A method for recycling waste polyester, in particular to a method for recycling waste polyester by a modified alcoholysis method to recycle waste polyester to prepare dimethyl terephthalate (DMT), is provided and belongs to waste polyester recycling technology field. The waste polyester after dewatering and deoxygenation treatment is used as a raw material, in the step of feeding in melted state the alcoholysis agent is added in the melted waste polyester for preliminary alcoholysis, and the alcoholysis agent is ethylene glycol. On one hand, alcoholysis reaction occurs when the waste polyester raw material are melted, and at the same time, the viscosity of the melted material is reduced. Thus, the melted material remains melted at the alcoholysis temperature and is not easy to solidify again after entering the alcoholysis tank, ensuring that the alcoholysis is carried out under homogeneous conditions.

Abstract: A disclosed method includes monitoring an audio signal energy level while having a noise suppressor deactivated to conserve battery power, buffering the audio signal in response to a detected increase in the audio energy level, activating and running a voice activity detector on the audio signal in response to the detected increase in the audio energy level and activating and running a noise estimator in response to voice being detected in the audio signal by the voice activity detector. The method may further include activating and running the noise suppressor only if the noise estimator determines that noise suppression is required. The method activates and runs a noise type classifier to determine the noise type based on information received from the noise estimator and selects a noise suppressor algorithm, from a group of available noise suppressor algorithms, where the selected noise suppressor algorithm is the most power consumption efficient.

Abstract: A device performs a method for using image data to aid voice recognition. The method includes the device capturing image data of a vicinity of the device and adjusting, based on the image data, a set of parameters for voice recognition performed by the device. The set of parameters for the device performing voice recognition include, but are not limited to: a trigger threshold of a trigger for voice recognition; a set of beamforming parameters; a database for voice recognition; and/or an algorithm for voice recognition. The algorithm may include using noise suppression or using acoustic beamforming.

Abstract: A disclosed method includes monitoring an audio signal energy level while having a noise suppressor deactivated to conserve battery power, buffering the audio signal in response to a detected increase in the audio energy level, activating and running a voice activity detector on the audio signal in response to the detected increase in the audio energy level and activating and running a noise estimator in response to voice being detected in the audio signal by the voice activity detector. The method may further include activating and running the noise suppressor only if the noise estimator determines that noise suppression is required. The method activates and runs a noise type classifier to determine the noise type based on information received from the noise estimator and selects a noise suppressor algorithm, from a group of available noise suppressor algorithms, where the selected noise suppressor algorithm is the most power consumption efficient.

Abstract: A device performs a method for using image data to aid voice recognition. The method includes the device capturing (302) image data of a vicinity of the device and adjusting (304), based on the image data, a set of parameters for voice recognition performed by the device (102). The set of parameters for the device performing voice recognition include, but are not limited to: a trigger threshold of a trigger for voice recognition; a set of beamforming parameters; a database for voice recognition; and/or an algorithm for voice recognition. The algorithm may include using noise suppression or using acoustic beamforming.

Abstract: A disclosed method includes monitoring an audio signal energy level while having a plurality of signal processing components deactivated and activating at least one signal processing component in response to a detected change in the audio signal energy level. The method may include activating and running a voice activity detector on the audio signal in response to the detected change where the voice activity detector is the at least one signal processing component. The method may further include activating and running the noise suppressor only if a noise estimator determines that noise suppression is required. The method may activate and runs a noise type classifier to determine the noise type based on information received from the noise estimator and may select a noise suppressor algorithm, from a group of available noise suppressor algorithms, where the selected noise suppressor algorithm is the most power consumption efficient.

Abstract: A method, a system, and a computer program product for preventing initiation of a voice recognition session. The method includes monitoring at least one audio output channel for at least one audio trigger phrase that initiates a voice recognition session. The method further includes in response to detecting the at least one audio trigger phrase on the at least one audio output channel, setting a logic state of at least one output trigger detector of the at least one audio output channel to a first state. The method further includes gating a logic state of at least one input trigger detector of at least one audio input channel to the first state for a time period and preventing initiation of a voice recognition session by the at least one audio trigger phrase on the at least one audio input channel while the logic state is the first state.

Abstract: A method, a system, and a computer program product for detecting an audio trigger phrase at a particular audio input channel and initiating a voice recognition session. The method includes capturing audio content by a plurality of microphone pairs of an audio capturing device, wherein each microphone pair of the plurality of microphone pairs is associated with an audio input channel of a plurality of audio input channels of the audio capturing device. The method further includes simultaneously monitoring, by a processor of the audio capturing device, audio content on each of the audio input channels. The method further includes: independently detecting, by the processor, an audio trigger phrase on at least one audio input channel of the plurality of audio input channels; and in response to detecting the audio trigger phrase, commencing a voice recognition session using the at least one audio input channel as an audio source.

Abstract: A device performs a method for using image data to aid voice recognition. The method includes the device capturing (302) image data of a vicinity of the device and adjusting (304), based on the image data, a set of parameters for voice recognition performed by the device (102). The set of parameters for the device performing voice recognition include, but are not limited to: a trigger threshold of a trigger for voice recognition; a set of beamforming parameters; a database for voice recognition; and/or an algorithm for voice recognition. The algorithm may include using noise suppression or using acoustic beamforming.

Abstract: A method, a system, and a computer program product reducing noise in audio received by at least one microphone. The method includes determining, from an audio signal received by at least one primary microphone of an electronic device, whether a user that is proximate to the electronic device is currently speaking. The method further includes, in response to determining that a user is not currently speaking, receiving a first audio using a first microphone subset from among a plurality of microphones and receiving at least one second audio using at least one second microphone subset from among the plurality of microphones. The method further includes generating a composite signal from the first audio and the second audio. The method further includes collectively processing the audio signal and the composite signal to generate a modified audio signal having a reduced level of noise.

Abstract: A method for controlling echo of a voice recognition system includes receiving at least two audio input signals corresponding to sound sensed by at least two microphones in a physical space. A first audio input signal of the at least two audio input signals is received on a primary channel, and each remaining audio input signal is received through a respective secondary channel. The method includes selecting, by a processor, based on an echo power level of a speaker in the physical space, a subset of echo control functions (ECFs) from among a plurality of ECFs of a multistage echo control system. Each ECF modifies the at least two audio input signals to reduce echo. The method includes generating a corresponding number of audio output signals by processing the signals received on the primary and secondary channels through the selected subset of ECFs, and outputting the audio output signals.

Abstract: A method for controlling echo of a voice recognition system includes receiving at least two audio input signals corresponding to sound sensed by at least two microphones in a physical space. A first audio input signal of the at least two audio input signals is received on a primary channel, and each remaining audio input signal is received through a respective secondary channel. The method includes selecting, by a processor, based on an echo power level of a speaker in the physical space, a subset of echo control functions (ECFs) from among a plurality of ECFs of a multistage echo control system. Each ECF modifies the at least two audio input signals to reduce echo. The method includes generating a corresponding number of audio output signals by processing the signals received on the primary and secondary channels through the selected subset of ECFs, and outputting the audio output signals.

Abstract: A method includes obtaining, by a processor, an audio echo signal and an audio desired signal from an acoustic echo correction stage of an electronic device, and converting the echo signal and the desired signal to the frequency domain. The method further includes grouping, by the processor, frequency bin results of respective frequency domain converted echo and desired signals into respective echo and desired sub-bands. A sub-band suppressor gain is estimated based on an estimated sub-band energy for the echo and desired sub-bands. The method further includes modulating the frequency domain converted desired signal to compensate for residual echo, the modulating based, at least in part, on the estimated sub-band suppressor gain, and the modulating producing a compensated frequency domain converted echo signal. The method also includes converting the compensated frequency domain converted desired signal into time domain converted audio output signal.

Abstract: A device performs a method for using image data to aid voice recognition. The method includes the device capturing (302) image data of a vicinity of the device and adjusting (304), based on the image data, a set of parameters for voice recognition performed by the device (102). The set of parameters for the device performing voice recognition include, but are not limited to: a trigger threshold of a trigger for voice recognition; a set of beamforming parameters; a database for voice recognition; and/or an algorithm for voice recognition. The algorithm may include using noise suppression or using acoustic beamforming.

Abstract: A method, a system, and a computer program product for detecting an audio trigger phrase at a particular audio input channel and initiating a voice recognition session. The method includes capturing audio content by a plurality of microphone pairs of an audio capturing device, wherein each microphone pair of the plurality of microphone pairs is associated with an audio input channel of a plurality of audio input channels of the audio capturing device. The method further includes simultaneously monitoring, by a processor of the audio capturing device, audio content on each of the audio input channels. The method further includes: independently detecting, by the processor, an audio trigger phrase on at least one audio input channel of the plurality of audio input channels; and in response to detecting the audio trigger phrase, commencing a voice recognition session using the at least one audio input channel as an audio source.

Abstract: A method includes obtaining, by a processor, an audio echo signal and an audio desired signal from an acoustic echo correction stage of an electronic device, and converting the echo signal and the desired signal to the frequency domain. The method further includes grouping, by the processor, frequency bin results of respective frequency domain converted echo and desired signals into respective echo and desired sub-bands. A sub-band suppressor gain is estimated based on an estimated sub-band energy for the echo and desired sub-bands. The method further includes modulating the frequency domain converted desired signal to compensate for residual echo, the modulating based, at least in part, on the estimated sub-band suppressor gain, and the modulating producing a compensated frequency domain converted echo signal. The method also includes converting the compensated frequency domain converted desired signal into time domain converted audio output signal.

Abstract: A method, a system, and a computer program product for preventing initiation of a voice recognition session. The method includes monitoring at least one audio output channel for at least one audio trigger phrase that initiates a voice recognition session. The method further includes in response to detecting the at least one audio trigger phrase on the at least one audio output channel, setting a logic state of at least one output trigger detector of the at least one audio output channel to a first state. The method further includes gating a logic state of at least one input trigger detector of at least one audio input channel to the first state for a time period and preventing initiation of a voice recognition session by the at least one audio trigger phrase on the at least one audio input channel while the logic state is the first state.