Some implementations involve receiving a content stream that includes audio data, determining a content type corresponding to the content stream and determining, based at least in part on the Receiving, by a control system and via an interface system, a content stream that includes audio data content type, a noise compensation method. Some examples involve performing the noise compensation method on the audio data to produce noise-compensated audio data, rendering the noise-compensated audio data for reproduction via a set of audio reproduction transducers of the audio environment, to produce rendered audio signals, and providing the rendered audio signals to at least some audio reproduction transducers of the audio environment.

An example speaker for providing alerts includes: a housing and a cover forming an integrated unit; a microphone configured to sense an ambient noise level; and a processor configured to adjust a volume of the speaker based upon the ambient noise level. A hinge can be positioned between the housing and the cover to allow the cover to be pivoted relative to the housing from a close position to an open position.

An example speaker for providing alerts includes: a housing and a cover forming an integrated unit; a microphone configured to sense an ambient noise level; and a processor configured to adjust a volume of the speaker based upon the ambient noise level. A hinge can be positioned between the housing and the cover to allow the cover to be pivoted relative to the housing from a close position to an open position.

The present disclosure relates to an automatic volume adjustment method and apparatus, a medium, and a device, which belong to the field of computer technologies, and can adjust the playback volume of audio or video. The automatic volume adjustment method includes: acquiring, in a case that a terminal does not output loudspeaker sound, a noise signal outside the terminal; determining noise energy based on the noise signal; and adjusting playback volume of audio or video on the terminal based on the noise energy.

The invention relates to a method for processing an acoustic input signal, preferably a speech signal, said method comprising the following steps: a) receiving a digital representation (S.sub.in) of an acoustic input signal, b) calculating at least one statistical parameter (P) of the digital representation (S.sub.in) of the acoustic input signal, c) calculating a compression ratio function (CR.sub.f) based—on a prescribed constant compression ratio (CR.sub.pr), said prescribed constant compression ratio (CR.sub.pr) uniformly mapping acoustic input signals of a selected magnitude to acoustic output signals of a selected magnitude, and—on at least one statistical parameter (P) calculated in step b), and d) applying the non-uniform compression ratio function (CR.sub.f) according to step c) on the digital representation (S.sub.in) of the acoustic input signal delivering a digital representation (S.sub.out) of an enhanced acoustic output signal.

A leveling equalizer includes a graphic equalizer circuit, a first multiplication circuit, a second multiplication circuit, an addition circuit, and a gain control circuit. The graphic equalizer circuit processes a first input signal and output a first output signal and a second output signal. The first multiplication circuit multiplies the first output signal and one of an adjustable gain value and a fixed gain value to generate a first adjusted output signal. The second multiplication circuit multiplies the second output signal and another of the adjustable gain value and the fixed gain value to generate a second adjusted output signal. The addition circuit combines the first adjusted output signal and the second adjusted output signal to generate an equalizer output signal. The gain control circuit dynamically adjusts the adjustable gain value according to the equalizer output signal.

A leveling equalizer includes a graphic equalizer circuit, a first multiplication circuit, a second multiplication circuit, an addition circuit, and a gain control circuit. The graphic equalizer circuit processes a first input signal and output a first output signal and a second output signal. The first multiplication circuit multiplies the first output signal and one of an adjustable gain value and a fixed gain value to generate a first adjusted output signal. The second multiplication circuit multiplies the second output signal and another of the adjustable gain value and the fixed gain value to generate a second adjusted output signal. The addition circuit combines the first adjusted output signal and the second adjusted output signal to generate an equalizer output signal. The gain control circuit dynamically adjusts the adjustable gain value according to the equalizer output signal.

A voice enhancing device amplifies and clarifies the voice of a user with hypophonia or other voice issues. The device includes a collar of either rigid or a soft material that is shaped to comfortably sit on the shoulders of the user. One or more microphone arrays are adjustably mounted to the collar to capture audio of the user talking. An electronics module enhances the captured audio signal and generates an enhanced audio signal that drives at least one speaker adjustably attached to the collar. The electronic controller implements one or more of an AGC amplifier to correct amplitude variation in spoked words, adaptive filtering to actively filter out background noise, a variable attack and decay function to improve intelligibility of the spoken words, a diphthong modification function to clarify the spoken words, and an echo cancelation function to reduce echo and feedback in the enhanced audio.

The present invention provides a deep learning based method and system for processing sound quality characteristics. The method comprises: obtaining data characteristics of an audio data to be processed by extracting features from user preference data including the audio data to be processed; based on the data characteristics, generating a sound quality processing result of the audio to be processed by using a trained baseline model; wherein the baseline model is a neural network model trained by using audio data behavioral data, and other relevant data from multiple users or a single user.

A content reproducing electronic apparatus includes a communicator including circuitry, an audio output device, and a processor configured to receive state information indicating a state of an external electronic apparatus from the external electronic apparatus located around the electronic apparatus via the communicator, obtain noise information corresponding to the received state information, and control the audio output device to output an audio signal of a content based on a volume corresponding to the obtained noise information.