The invention provides a method for detecting music in audio speech processing by decomposing an audio signal into component signals in one or more bandwidths. The invention then detects energy levels across preselected time and frequency windows within the narrowest bandwidth components. A predetermined number of detections at predetermined detection levels will result in the likely characterization of music being present in that window.

A sensor processing unit comprises a microphone and a sensor processor. The sensor processor is coupled with the microphone. The sensor processor is configured to operate the microphone to capture an audio sample from an environment in which the microphone is disposed. The sensor processor is configured to perform music activity detection on the audio sample to detect for music within the audio sample. Responsive to detection of music within the audio sample, the sensor processor is configured to send a music detection signal to an external processor located external to the sensor processing unit, the music detection signal indicating that music has been detected in the environment.

Equalizer controller and controlling method are disclosed. In one embodiment, an equalizer controller includes an audio classifier for identifying the audio type of an audio signal in real time; and an adjusting unit for adjusting an equalizer in a continuous manner based on the confidence value of the audio type as identified.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech recognition using complex linear projection are disclosed. In one aspect, a method includes the actions of receiving audio data corresponding to an utterance. The method further includes generating frequency domain data using the audio data. The method further includes processing the frequency domain data using complex linear projection. The method further includes providing the processed frequency domain data to a neural network trained as an acoustic model. The method further includes generating a transcription for the utterance that is determined based at least on output that the neural network provides in response to receiving the processed frequency domain data.

A method of operating a hearing aid system (400) based on a classification of the current sound environment, which includes a measure of a beat probability and a hearing aid system for carrying out such a method.

Provided is a signal processing apparatus including a feature detection unit configured to detect, from an input signal, a detection signal including at least one of audience-generated-sound likelihood and music likelihood, a reverberation adding unit configured to add long or short reverberations to the input signal based on a detected tone being moderate or ordinary tone respectively, and a vicinity-sound generation unit configured to generate vicinity sound based on the detection signal.

Apparatus and methods for audio classifying and processing are disclosed. In one embodiment, an audio processing apparatus includes an audio classifier for classifying an audio signal into at least one audio type in real time; an audio improving device for improving experience of audience; and an adjusting unit for adjusting at least one parameter of the audio improving device in a continuous manner based on the confidence value of the at least one audio type.

A content processing device is provided. The content processing device includes a receiver configured to receive a content, an audio processor configured to extract an audio signal by decoding audio data included in the content, a processor configured to determine a characteristic section in the audio signal based on a ratio of music information of the audio signal, and detect a segment corresponding to the characteristic section in the audio signal; and a communicator configured to transmit the segment to a music recognition server, and a size of the segment is determined variably within a threshold range.

Systems, devices, and methods, etc., that provide digital audio toolboxes, music kits, digital audio tracks, etc., herein supply digital audio tracks such as music for combination with and synchronization with digital pre-existing media tracks. The toolkits, etc., herein provide users with visual tracks in media, to create, provide and/or synchronize precisely timed tracks used in audio media productions, or otherwise to provide multiple, precisely timed and synced tracks where a music/sound design track from the toolkits is added to a pre-made media track such as a visual footage.

According to one embodiment, an electronic device includes a receiver and a hardware processor. The receiver is configured to receive an audio signal. The hardware processor is configured to enable a first function comprising separating the audio signal into a voice signal and a background sound signal and emphasizing or suppressing either the voice signal or the background sound signal and enable a second function comprising giving an acoustic effect to the audio signal. The hardware processor is further configured to receive an user operation to turn on either the first function or the second function and restrict the second function, if the first function is turned on.