A sound signal detection device is closed. The sound signal detection device is connected between an audio output device and a speaker apparatus. The sound signal detection device includes a first connecting port, a second connecting port, a microphone, and a processing module. The first connecting port connects to the audio output device and acquires a first sound signal. The second connecting port is used for outputting the first sound signal to the speaker apparatus. The microphone is used for receiving a second sound signal from the speaker apparatus. The process module is electrically connected to the microphone and used for detecting a volume of the second sound signal to generate a real volume signal.

Implementations generally relate to automated equalizer adjustments based on audio characteristics. In some implementations, a method includes detecting music that is being currently played on an audio device. The method further includes adjusting one or more equalizer settings of an equalizer device based at least in part on a music genre associated with the music. The method further includes outputting the music based at least in part on the adjusting of the one or more equalizer settings of the equalizer device.

Example embodiments disclosed herein relate to separated audio analysis and processing. A system for processing an audio signal is disclosed. The system includes an audio analysis module configured to analyze an input audio signal to determine a processing parameter for the input audio signal, the input audio signal being represented in time domain. The system also includes an audio processing module configured to process the input audio signal in parallel with the audio analysis module. The audio processing module includes a time domain filter configured to filter the input audio signal to obtain an output audio signal in the time domain, and a filter controller configured to control a filter coefficient of the time domain filter based on the processing parameter determined by the audio analysis module. Corresponding method and computer program product of processing an audio signal are also disclosed.

In device having at least one microphone and one or more speakers, environmental sound may be recorded using the microphone, classified and mixed with source media sound to produce a mixed sound depending on the classification. The mixed sound may then be played over the one or more speakers.

Methods, apparatus, systems and articles of manufacture are disclosed to adjust audio playback settings based on analysis of audio characteristics. Example apparatus disclosed herein include an equalization (EQ) model query generator to generate a query to a neural network, the query including a representation of a sample of an audio signal; an EQ filter settings analyzer to: access a plurality of audio playback settings determined by the neural network based on the query; and determine a filter coefficient to apply to the audio signal based on the plurality of audio playback settings; and an EQ adjustment implementer to apply the filter coefficient to the audio signal in a first duration.

Methods, apparatus, systems and articles of manufacture are disclosed to adjust audio playback settings. Example apparatus disclosed herein include an equalization (EQ) model query generator to generate a query to a neural network, the query including a representation of a sample of an audio signal; an EQ filter settings analyzer to: access a plurality of audio playback settings determined by the neural network based on the query; and determine a filter coefficient to apply to the audio signal based on the plurality of audio playback settings; an EQ personalization manager to; generate a personalized EQ setting; and an EQ adjustment implementor to: blend the personalized EQ setting and the filter coefficient to generate a blended equalization; and apply the blended equalization to the audio signal in a first duration.

Methods, apparatus, systems and articles of manufacture are disclosed for playback using pre-processed profile information and personalization. Example apparatus disclosed herein include a synchronizer to, in response to receiving a media signal to be played on a playback device, access an equalization (EQ) profile corresponding to the media signal; an EQ personalization manager to generate a personalized EQ setting; and an EQ adjustment implementor to modify playback of the media signal on the playback device based on a blended equalization generated based on the EQ profile and the personalized EQ setting.

Methods, apparatus, systems and articles of manufacture are disclosed for audio equalization. Example apparatus disclosed herein include a volume adjuster to apply equalization adjustments to an audio signal to generate an equalized audio signal, the equalization adjustments output from a neural network in response to an input feature set; a thresholding controller to: detect an irregularity in a frequency representation of the audio signal after application of the equalization adjustments, the irregularity corresponding to a change in volume between adjacent frequency values exceeding a threshold; and adjust a volume at a first frequency value of the adjacent frequency values to reduce the irregularity; an equalization (EQ) curve generator to generate an EQ curve to apply to the audio signal when the irregularity has been reduced; and a frequency to time domain converter to output the equalized audio signal in a time domain based on the EQ curve.

A networked speaker system automatically adjusts certain audio speaker system settings based on whether the system is inside a building or has been moved outside as may be sensed by one or capacitors on a speaker. Also, techniques are described for adjusting speaker driver direction based on walls or other barriers in a room or based on the location of a listener.

Systems and methods for adaption of telephonic signal are provided. A telephonic listener's demographic information is first received. Next, a set of preset parameters are retrieved from a database based on the demographic information. The preset parameters are calculated using suprathreshold and/or threshold hearing data, which is representative of a demographic group. These preset parameters are then outputted to a sound personalization digital signal processing (DSP) algorithm. A voice signal is then processed using the sound personalization DSP and the processed voice signal is then outputted at the listener's telephonic device.