Abstract: A method, computer program, and computer system is provided for an all-deep-learning based AEC system by recurrent neural networks. The model consists of two stages, echo estimation stage and echo suppression stage, respectively. Two different schemes for echo estimation are presented herein: linear echo estimation by multi-tap filtering on far-end reference signal and non-linear echo estimation by single-tap masking on microphone signal. A microphone signal waveform and a far-end reference signal waveform are received. An echo signal waveform is estimated based on the microphone signal waveform and a far-end reference signal waveform. A near-end speech signal waveform is output based on subtracting the estimated echo signal waveform from the microphone signal waveform, and echoes are suppressed within the near-end speech signal waveform.

Abstract: A method and apparatus comprising computer code configured to cause a processor or processors to receive multiple audio signals obtained from ones of a plurality of microphones of a microphone array, implement an audio zooming based on the audio signals by selectively focusing and enhancing first ones of the audio signals and by attenuating other ones of the audio signals, and control an output of audio based on the audio zooming, and the audio zooming includes a consolidating of a plurality of directional features of the first ones of the audio signals within a field around the microphone array and a countering based on determining directional aspects of the other ones of the audio signals from outside of the field.

Abstract: A method and apparatus comprising computer code configured to cause a processor or processors to receive an audio signal obtained from a microphone, input the audio signal into a neural-network pipeline, the neural-network pipeline including a convolutional network that receives the audio signal and provides a first output of the convolutional network to an enhancer, the enhancer including a deep complex convolutional recurrent network that receives the first output along with a mel spectrogram of the audio signal and outputs a second output to at least one of a vocoder and a decoder, and control an output of an enhanced audio signal from the at least one of the vocoder and the decoder.

Abstract: A method performed by at least one processor of an acoustic howling suppression (AHS) system includes receiving, from an input source device, an audio signal. The method includes refining one or more parameters of a Kalman filter based on one or more neural networks. The method includes filtering the audio signal using the Kalman filter with the one or more refined parameters of the Kalman filter to reduce acoustic howling included in the audio signal.

Abstract: A method and apparatus comprising computer code configured to cause a processor or processors to receive an audio signal obtained from a microphone, input the audio signal into a neural-network based AHS model, train the neural-network based AHS model based on input signals which are recursively generated from the audio signal during training of the AHS model, and output an AHS signal from the neural-network based AHS model in which AHS is applied to the audio signal, wherein the AHS signal is a version of the audio signal in which acoustic howling noise of the audio signal is suppressed and target audio of the audio signal is sustained.

Abstract: A method of manufacturing a semiconductor device includes: forming a substrate over the substrate, the substrate defining a logic region and a memory region; depositing a bottom electrode layer across the logic region and the memory region; depositing a magnetic tunnel junction (MTJ) layer over the bottom electrode layer; depositing a first conductive layer over the MTJ layer; depositing a sacrificial layer over the first conductive layer; etching the sacrificial layer in the memory region to expose the first conductive layer in the memory region while keeping the first conductive layer in the logic region covered; depositing a second conductive layer in the memory region and the logic region; patterning the second conductive layer to expose the MTJ layer in the memory region; and etching the patterned second conductive layer and the MTJ layer to form a top electrode and an MTJ, respectively, in the memory region.

Abstract: A heat dissipation assembly is disclosed and includes a frame and a fan. The frame includes a heat conduction channel and an airflow intake. The heat conduction channel is communication with an exterior through airflow intake. The frame includes a first plane, a second plane and an inclined plane. The first plane is disposed adjacent to the airflow intake. The inclined plane is connected between the first plane and the second plane. The second plane includes an inlet. The heat conduction channel is in communication between the airflow intake and the inlet. A cross-section area of the heat conduction channel adjacent to the airflow intake is greater than that of the heat conduction channel adjacent to the inlet. The fan is spatially corresponding to the inlet, and assembled with the frame to form an outlet in communication with the airflow intake and the heat conduction channel through the inlet.

Abstract: The invention generally relates to solid forms of berberine ursodeoxycholate, and to pharmaceutical compositions, and methods of preparation and therapeutic use thereof. In particular, the invention relates to solid forms of berberine ursodeoxycholate and pharmaceutical compositions thereof useful in treating and/or preventing various diseases or disorders, including metabolic disorders, heart diseases, neurodegenerative diseases and liver diseases.

Abstract: An object processing method and apparatus, an electronic device and a medium are provided. The method includes: displaying an object-to-be-processed selection interface; in response to a confirmation control in the object-to-be-processed selection interface being triggered, displaying an initial attribute selection interface of a selected object to be processed; in response to the target attribute control in the initial attribute selection interface being triggered, displaying an initial attribute changing interface; and in response to a processing of the selected object to be processed through the initial attribute changing interface satisfying a first preset condition, displaying a target attribute processing interface.

Abstract: A liquid cooling vapor chamber heat dissipation module includes a liquid cooling cover, a metallic top cover, and a metallic bottom cover. The liquid cooling cover includes a top portion, a sidewall and an accommodating space. The sidewall includes a liquid inlet and a liquid outlet. The outer heat-dissipating surface of the top cover has a plurality of columnar heat-dissipating structures. The inner evaporation surface of the metallic bottom cover has parallel bottom grooves and protrusive supporting structures disposed between the bottom grooves. An integrated vapor chamber is formed by engaging the metallic top and bottom covers. The liquid cooling cover engages with the outer heat-dissipating surface of the metallic top cover with the columnar heat-dissipating structures accommodating within the accommodating space, which allows cooling liquid to enter the accommodating space from the liquid inlet and flow through the columnar heat-dissipating structures, and flow out from the liquid outlet.

Abstract: An expansion reinforcing plate and a paving method therefor, the expansion reinforcing plate comprising plates and an elastic inserting strip assembling structure; the elastic inserting strip assembling structure comprises expansion reinforcing connecting strips A (1), expansion reinforcing connecting strips B (2) and expansion reinforcing connecting strip assembling groove structures (3); the expansion reinforcing connecting strips A (1) are inserted into the expansion reinforcing connecting strip assembling groove structures (3) of two adjacent plates; the expansion reinforcing connecting strips A (1) of every two adjacent plates are jointly connected with the expansion reinforcing connecting strips B (2); the expansion reinforcing connecting strips B (2) make contact with the expansion reinforcing connecting strips A (1) on the two sides for reaction, so that the expansion reinforcing connecting strips A (1) and the expansion reinforcing connecting strips B (2) expand and are fixedly connected, and then th

Abstract: A semiconductor device includes a substrate, a semiconductor nanostructure over the substrate, a gate dielectric layer wrapping around the semiconductor nanostructure and a gate electrode over the gate dielectric layer. The semiconductor nanostructure includes a plurality of first strips extending along a first direction and a plurality of second strips along a second direction, and wherein the second direction crosses the first direction.

Abstract: A method and apparatus comprising computer code configured to cause a processor or processors to receive an audio signal obtained from a microphone, input the audio signal into a neural-network based AEC model, and output an AEC signal from the neural-network based AEC model in which AEC is applied to the audio signal, and the AEC signal is a version of the audio signal in which acoustic echo noise of the audio signal is suppressed and target audio of the audio signal is sustained.

Abstract: A method and apparatus comprising computer code configured to cause a processor or processors to receive an audio signal obtained from a microphone, input the audio signal into a neural-network based AHS model, wherein the neural-network based AHS model is trained using a training audio signal, and output an AHS signal from the neural-network based AHS model in which AHS is applied to the audio signal, wherein the AHS signal is a version of the audio signal in which acoustic howling noise of the audio signal is suppressed and target audio of the audio signal is sustained.

Abstract: This disclosure is a stator assembly of a water pump. The stator assembly includes a shell seat and a stator component. The shell seat includes an inner side wall and hooks. The stator component includes a bobbin, a silicon lamination set and a wiring set. The bobbin covers the silicon lamination set and exposes an outer peripheral surface of the silicon lamination set. The wiring set is arranged on the bobbin, and snapping holes are disposed on a bottom side of the bobbin. The inner side wall is attached to the outer peripheral surface, and the snapping holes are engaged with the hooks. Therefore, the stator component may be firmly integrated into the shell seat through simple positioning structures.

Abstract: A method, computer system, and computer readable medium are provided for activating speech recognition based on keyword spotting (KWS). Waveform data corresponding to one or more speakers is received. One or more direction features are extracted from the received waveform data. One or more keywords are determined from the received waveform data based on the one or more extracted features. Speech recognition is activated based on detecting the determined keyword.

Abstract: Method, apparatus, and non-transitory storage medium for training a deep neural-network model jointly for acoustic echo suppression and acoustic howling suppression are provided. The method may include generating a teacher speech signal for training the deep neural-network model based on a input speech from a speech system and at least one reference signal. The deep neural-network model is trained jointly for both acoustic echo suppression and acoustic howling suppression by using the teacher speech signal and a correlation loss. During training of the deep neural-network model, the training task formulates a recurrent feedback suppression process as an instantaneous speech separation task using the teacher-forced training strategy.

Abstract: Method, apparatus, and non-transitory storage medium for hybrid acoustic howling suppression based on a frequency filter model and a deep neural network are provided. The method may include receiving a speech signal, the speech signal including target speech, feedback, and noise, and inputting the speech signal into a trained hybrid neural-network based howling suppression model, wherein the trained hybrid neural-network based howling suppression model is trained using training speech signal and pre-processed acoustic feedback from a first frequency filter model. The method may also include generating an enhanced speech signal with suppressed howling as an output of the trained hybrid neural-network based howling suppression model, wherein the enhanced speech signal is used to update parameters of the first frequency filter model.

Abstract: The invention generally relates to solid forms of berberine ursodeoxycholate, and to pharmaceutical compositions, and methods of preparation and therapeutic use thereof. In particular, the invention relates to solid forms of berberine ursodeoxycholate and pharmaceutical compositions thereof useful in treating and/or preventing various diseases or disorders, including metabolic disorders, heart diseases, neurodegenerative diseases and liver diseases.

Abstract: The present disclosure describes a method of fabricating a semiconductor structure that includes forming a dummy gate structure over a substrate, forming a first spacer on a sidewall of the dummy gate structure and a second spacer on the first spacer, forming a source/drain structure on the substrate, removing the second spacer, forming a dielectric structure over the source/drain structure, replacing the dummy gate structure with a metal gate structure and a capping structure on the metal gate structure, and forming an opening in the dielectric structure. The opening exposes the source/drain structure. The method further includes forming a dummy spacer on a sidewall of the opening, forming a contact structure in the opening, and removing the dummy spacer to form an air gap between the contact structure and the metal gate structure. The contact structure is in contact with the source/drain structure in the opening.