Audio processing method and audio processing apparatus, and training method are described. According to embodiments of the application, an accent identifier is used to identify accent frames from a plurality of audio frames, resulting in an accent sequence comprised of probability scores of accent and/or non-accent decisions with respect to the plurality of audio frames. Then a tempo estimator is used to estimate a tempo sequence of the plurality of audio frames based on the accent sequence. The embodiments can be well adaptive to the change of tempo, and can be further used to tracking beats properly.

A method and system are provided for extracting features from digital audio signals which exhibit variations in pitch, timbre, decay, reverberation, and other psychoacoustic attributes and learning, from the extracted features, an artificial neural network model for generating contextual latent-space representations of digital audio signals. A method and system are also provided for learning an artificial neural network model for generating consistent latent-space representations of digital audio signals in which the generated latent-space representations are comparable for the purposes of determining psychoacoustic similarity between digital audio signals. A method and system are also provided for extracting features from digital audio signals and learning, from the extracted features, an artificial neural network model for generating latent-space representations of digital audio signals which take care of selecting salient attributes of the signals that represent psychoacoustic differences between the signals.

A method of making audio music selection and creating a mixtape, comprising importing song files from a song repository; sorting and filtering the song files based on selection criteria; and creating the mixtape from the song files sorting and filtering results. The sorting and filtering of the song files comprise: spectral analyzing each of the song files to extract low level acoustic feature parameters of the song file; from the low level acoustic feature parameter values, determining the high level acoustic feature parameters of the analyzed song file; determining a similarity score of each of the analyzed song files by comparing the acoustic feature parameter values of the analyzed song file against desired acoustic feature parameter values determined from the selection criteria; and sorting the analyzed song files according to their similarity scores; and filtering out the analyzed song files with first similarity scores lower than a filter threshold.

An electronic device may comprise audio processing circuitry, pace tracking circuitry, and positioning circuitry. The pace tracking circuitry may be operable to selects songs to be processed for playback, and/or control time stretching applied to such songs, by the audio processing circuitry based on position data generated by the positioning circuitry, a desired tempo, and whether the songs are stored locally or network-accessible. The position data may indicate the pace of a runner during a preceding, determined time interval. The pace tracking circuitry may control the song selection and/or time stretching based on a runner profile data stored in memory of the music device. The profile data may include runner's distance-per-stride data. The electronic device may include sensors operable to function as a pedometer. The pace tracking circuitry may update the distance-per-stride data based on the position data and based on data output by the one or more sensors.

A method for processing music audio data, including providing input audio data representing a first piece of music comprising a mixture of musical timbres. The method also includes decomposing the input audio data to generate at least first-timbre decomposed data representing a first timbre selected from the musical timbres of the first piece of music, and second-timbre decomposed data representing a second timbre selected from the musical timbres of the first piece of music. The method also includes applying a transport control to obtain transport controlled first-timbre decomposed data. The method also includes recombining audio data obtained from the transport controlled first-timbre decomposed data with audio data obtained from the second-timbre decomposed data to obtain recombined audio data.

An automatic performance system includes a sign detector configured to detect a sign action of a performer performing a musical piece, a performance analyzer configured to sequentially estimates a performance position in the musical piece by analyzing an acoustic signal representing performed sound in parallel with the performance, and a performance controller configured to control an automatic performance device to carry out an automatic performance of the musical piece so that the automatic performance is synchronized with the sign action detected by the sign detector and a progress of the performance position estimated by the performance analyzer.

A media-playback device acquires a heart rate, selects a song with a first tempo, and initiates playback of the song. The song meets a set of qualification criteria and the first tempo is based on the heart rate, such as being equal to or less than the heart rate. The media-playback device also initiates playback of a binaural beat at a first frequency. Over a period of time, the binaural beat's first frequency is changed to a second frequency. Over the period of time, the first tempo can also be changed to a second tempo, where the second tempo is slower than the first tempo.

The intelligent accompaniment generating system includes an input module, an analysis module, a generation module and a musical equipment. The input module is configured to receive a musical pattern signal derived from a raw signal. The analysis module is configured to analyze the musical pattern signal to extract a set of audio features, wherein the input module is configured to transmit the musical pattern signal to the analysis module. The generation module is configured to obtain a playing assistance information having an accompaniment pattern from the analysis module, wherein the accompaniment pattern has at least two parts having different onsets therebetween, and each onsets of the at least two parts is generated by an algorithm according to the set of audio features. The musical equipment includes a digital amplifier configured to output an accompaniment signal according to the accompaniment pattern.

A timing unit and method useable with a computer and user input includes a circuit and a timer. The timer establishes a reference signal having periodic occurrence and receives a trigger signal from the user input. The circuit generates information that represents the periodic occurrences of the reference signal and response timing data representing a relationship between the trigger signal and one of the occurrences. A communication channel is provided between the circuit and the computer.

A system encourages experimentation with audio frequency and speaker technologies while causing an inanimate figure to appear to dance. The system applies a bandpass filter to an incoming audio stream (e.g., in a low frequency bass band). The system monitors the magnitude of the audio content in a frequency band of interest. When an amplitude peak or other threshold magnitude is detected, a controller injects a short pulse (e.g., 3 cycles) of a sub-audible low frequency sine wave to a platform. Preferably, the sub-audible low frequency sine wave is at a resonance frequency of the platform to maximize its movement. The figure is positioned on the platform and appears to dance to the beat of the music.