Abstract: A mobile terminal, including an NFC antenna. The NFC antenna includes a feed, an inductor and a capacitor that are connected in parallel to the feed. The NFC antenna includes one or more of a first distributed inductor, a second distributed inductor, a third distributed inductor, and a fourth distributed inductor. The first distributed inductor is located between the feed and the inductor, the second distributed inductor is located between the inductor and a first ground point, the third distributed inductor is located between the feed and the capacitor, and the fourth distributed inductor is located between the capacitor and a second ground point. The inductor includes a lumped inductor and a metal segment connected to the lumped inductor in series.

Abstract: A method, an apparatus and a device for converting a whispered speech, and a readable storage medium are provided. The method is implemented based on the whispered speech converting model. The whispered speech converting model is trained in advance by using recognition results and whispered speech training acoustic features of whispered speech training data as samples and using normal speech acoustic features of normal speech data parallel to the whispered speech training data as sample labels. A whispered speech acoustic feature and a preliminary recognition result of whispered speech data are acquired, then the whispered speech acoustic feature and the preliminary recognition result are inputted into a preset whispered speech converting model to acquire a normal speech acoustic feature outputted by the model. In this way, the whispered speech can be converted to a normal speech.

Abstract: An echo cancellation method based on delay estimation is provided. In the method, a microphone signal and a reference signal are received and preprocessed. In the preprocessed microphone signal and the preprocessed reference signal, frequency point signals with non-linearity in a current echo cancellation scenario are determined. A current delay estimation value is calculated based on frequency point signals without non-linearity in the microphone signal and the reference signal. The reference signal is shifted based on the current delay estimation value. An adaptive filter is updated based on the preprocessed microphone signal and the shifted reference signal, to perform echo cancellation.

Abstract: A target voice detection method and a target voice detection apparatus are provided. The method includes: receiving sound signals collected by a microphone array; performing a beamforming process on the sound signals to obtain beams in different directions; extracting a detection feature of each frame based on the sound signals and the beams in different directions; inputting an extracted detection feature of a current frame into a pre-constructed target voice detection model to obtain a model output result; and obtaining a target voice detection result of the current frame based on the model output result.

Abstract: A mobile terminal, including an NFC antenna. The NFC antenna includes a feed, an inductor and a capacitor that are connected in parallel to the feed. The NFC antenna includes one or more of a first distributed inductor, a second distributed inductor, a third distributed inductor, and a fourth distributed inductor. The first distributed inductor is located between the feed and the inductor, the second distributed inductor is located between the inductor and a first ground point, the third distributed inductor is located between the feed and the capacitor, and the fourth distributed inductor is located between the capacitor and a second ground point. The inductor includes a lumped inductor and a metal segment connected to the lumped inductor in series.

Abstract: A microphone array-based target voice acquisition method and device, said method comprising: receiving voice signals acquired on the basis of a microphone array (101); determining a pre-selected target voice signal and a direction thereof (102); performing strong directional gain and weak directional gain on the pre-selected target voice signal, so as to obtain a strong gain signal and a weak gain signal (103); performing an endpoint detection on the basis of the strong gain signal, so as to obtain an endpoint detection result (104); and performing endpoint processing on the weak gain signal according to the endpoint detection result, so as to obtain a final target voice signal (105). The present invention can obtain an accurate and reliable target voice signal, thereby avoiding an adverse effect of the target voice quality on subsequent target voice processing.

Abstract: Provided are a voice denoising method and apparatus, a server and a storage medium. The voice denoising method comprises: acquiring voice signals synchronously collected by an acoustic microphone and a non-acoustic microphone (S100); carrying out voice activity detection according to the voice signal collected by the non-acoustic microphone to obtain a voice activity detection result (S110); and according to the voice activity detection result, denoising the voice signal collected by the acoustic microphone to obtain a denoised voice signal (S120). The effect of denoising can be enhanced, and the quality of voice signals can be improved.

Abstract: An echo cancellation method based on delay estimation is provided. In the method, a microphone signal and a reference signal are received and preprocessed. In the preprocessed microphone signal and the preprocessed reference signal, frequency point signals with non-linearity in a current echo cancellation scenario are determined. A current delay estimation value is calculated based on frequency point signals without non-linearity in the microphone signal and the reference signal. The reference signal is shifted based on the current delay estimation value. An adaptive filter is updated based on the preprocessed microphone signal and the shifted reference signal, to perform echo cancellation.

Abstract: Provided are a voice denoising method and apparatus, a server and a storage medium. The voice denoising method comprises: acquiring voice signals synchronously collected by an acoustic microphone and a non-acoustic microphone (S100); carrying out voice activity detection according to the voice signal collected by the non-acoustic microphone to obtain a voice activity detection result (S110); and according to the voice activity detection result, denoising the voice signal collected by the acoustic microphone to obtain a denoised voice signal (S120). The effect of denoising can be enhanced, and the quality of voice signals can be improved.

Abstract: A target voice detection method and a target voice detection apparatus are provided. The method includes: receiving sound signals collected by a microphone array; performing a beamforming process on the sound signals to obtain beams in different directions; extracting a detection feature of each frame based on the sound signals and the beams in different directions; inputting an extracted detection feature of a current frame into a pre-constructed target voice detection model to obtain a model output result; and obtaining a target voice detection result of the current frame based on the model output result.

Abstract: A microphone array-based target voice acquisition method and device, said method comprising: receiving voice signals acquired on the basis of a microphone array (101); determining a pre-selected target voice signal and a direction thereof (102); performing strong directional gain and weak directional gain on the pre-selected target voice signal, so as to obtain a strong gain signal and a weak gain signal (103); performing an endpoint detection on the basis of the strong gain signal, so as to obtain an endpoint detection result (104); and performing endpoint processing on the weak gain signal according to the endpoint detection result, so as to obtain a final target voice signal (105). The present invention can obtain an accurate and reliable target voice signal, thereby avoiding an adverse effect of the target voice quality on subsequent target voice processing.

Abstract: A method, an apparatus and a device for converting a whispered speech, and a readable storage medium are provided. The method is implemented based on the whispered speech converting model. The whispered speech converting model is trained in advance by using recognition results and whispered speech training acoustic features of whispered speech training data as samples and using normal speech acoustic features of normal speech data parallel to the whispered speech training data as sample labels. A whispered speech acoustic feature and a preliminary recognition result of whispered speech data are acquired, then the whispered speech acoustic feature and the preliminary recognition result are inputted into a preset whispered speech converting model to acquire a normal speech acoustic feature outputted by the model. In this way, the whispered speech can be converted to a normal speech.

Abstract: Methods and compositions, e.g., therapeutic agents, are provided for modulating gene and/or protein expression of Forkhead Box protein 1 (Foxp1), particularly Foxp1A and Foxp1D, in CD4+ T cells. Such modulation permits manipulation of the B cell response and antibody production and activity, without depleting the number, production or activity of the T cells. In one aspect, methods and compositions for increasing or up regulating the nucleic acid and/or protein expression of Foxp1A, Foxp1D or a combination thereof in the subject's cells in vivo, inhibits or suppresses B cell response and antibody production or activity thereof in the subject.