Coordinated audio and video filter pairs are applied to enhance artistic and emotional content of audiovisual performances. Such filter pairs, when applied in audio and video processing pipelines of an audiovisual application hosted on a portable computing device (such as a mobile phone or media player, a computing pad or tablet, a game controller or a personal digital assistant or book reader) can allow user selection of effects that enhance both audio and video coordinated therewith. Coordinated audio and video are captured, filtered and rendered at the portable computing device using camera and microphone interfaces, using digital signal processing software executable on a processor and using storage, speaker and display devices of, or interoperable with, the device. By providing audiovisual capture and personalization on an intimate handheld device, social interactions and postings of a type made popular by modern social networking platforms can now be extended to audiovisual content.

Improvisation or playing along with a musical group or with a song is enjoyable to people and musicians of all ability levels. However, it is easy to play notes which do not harmonize with other notes and pitches which are being played. Provided herein is a method, computer program product and electronic device for assigning a set of pitches to a plurality of cells of an electronic device having a touch screen input device. The method may include the steps of obtaining an input chord, disassembling the chord into at least one base note and a plurality of individual voices, arranging a predetermined number of voices of the chord according to at least one predefined rule, and assigning at least one set of pitches to a plurality of cells of an electronic device, said set of pitches corresponding to the base note and arranged predetermined number of voices of the chord. The present method allows a musician to freely play along without the possibility of playing an errant note as the user does not control the actual pitch associated with the cells being indicated by a user on the touch screen.

Systems, including methods and apparatus, for generating audio effects based on accompaniment audio produced by live or pre-recorded accompaniment instruments, in combination with melody audio produced by a singer. Audible broadcast of the accompaniment audio may be delayed by a predetermined time, such as the time required to determine chord information contained in the accompaniment signal. As a result, audio effects that require the chord information may be substantially synchronized with the audible broadcast of the accompaniment audio. The present teachings may be especially suitable for use in karaoke systems, to correct and add sound effects to a singer's voice that sings along with a pre-recorded accompaniment track.

Systems and/or computer-implemented methods search, compare and/or match digital audio files, wherein the systems and/or methods provide a group of digital audio tracks to a computer system, wherein the group is provided to the computer system as input files or stored in a database associated with the computer system, wherein the group comprises a first digital audio track and a second digital audio track, wherein the first digital audio track is a live recording of a song and the second digital audio track is a previously recorded studio recording of a song. Moreover, the systems and methods compare audio features of the first and second digital audio tracks to determine whether the first and second digital audio tracks are a match comprising same performances of a same song or different performances of the same song, and output bounds for the match when the first and second digital audio tracks are determined to match, wherein the bounds for the match comprise start and end times for the match in both the first and second digital audio tracks.

A platform or system is disclosed for performing musical analysis to detect musical properties in received live or pre-recorded audio data. The analysis can include a synchronous analysis for generating estimated one or more transitory musical properties and an asynchronous analysis for generating one or more aggregate musical properties which can be applied to the transitory musical properties to generate confirmed musical properties, which can be stored as metadata associated with an audio file. In some cases, live audio data can be received, recorded, dynamically analyzed to provide realtime metadata (e.g., to a display), then the realtime metadata can be analyzed to provide confirmed, updated, or validated metadata. In some cases, initial analysis (e.g., dynamic analysis) can determine chord estimates, usable in further analysis (e.g., offline analysis) to estimate a musical key, which can then be applied to the chord estimates to determine the most likely chord estimates and determine chord progressions.

A platform or system is disclosed for performing musical analysis to detect musical properties in received live or pre-recorded audio data. The analysis can include a synchronous analysis for generating estimated one or more transitory musical properties and an asynchronous analysis for generating one or more aggregate musical properties which can be applied to the transitory musical properties to generate confirmed musical properties, which can be stored as metadata associated with an audio file. In some cases, live audio data can be received, recorded, dynamically analyzed to provide realtime metadata (e.g., to a display), then the realtime metadata can be analyzed to provide confirmed, updated, or validated metadata. In some cases, initial analysis (e.g., dynamic analysis) can determine chord estimates, usable in further analysis (e.g., offline analysis) to estimate a musical key, which can then be applied to the chord estimates to determine the most likely chord estimates and determine chord progressions.

A music composition and training system includes: identifying a first chord of a chord progression. Then, for multiple iterations, the system includes selecting a chord of the chord progression, beginning with the identified first chord, and: identifying one or more potential subsequent chords in such a way that each of the potential subsequent chords provide a musical progression; applying weighted criteria to each of the potential subsequent chords; selecting a second chord based on the weighting while also providing variety and unpredictability; and combining the second chord into the chord progression. The system then uses the generated chord progression to generate or teach music.

Performance information of one or more accompaniment parts is extracted from original performance information. Arranged accompaniment performance information is created using, in accordance with a predetermined arranging condition, only any one or more of pitch names included in the extracted accompaniment performance information. The predetermined arranging condition comprises instructing that any of chord component notes be thinned out in an identified chord progression, and arranged accompaniment performance information is created by thinning out an accompaniment note of a pitch name corresponding to the chord component note having been instructed to be thinned out. Another predetermined arranging condition comprises setting a ratio between chords and arpeggios in one or more measures, and a combination of chords and arpeggios in the extracted accompaniment part performance information is changed so that a ratio between chords and arpeggios in one or more measures in the extracted accompaniment performance information assumes the set ratio.

Described are methods and systems of identifying one or more fundamental frequency component(s) of an audio signal. The methods and systems may include any one or more of an audio event receiving step, a signal discretization step, a masking step, and/or a transcription step.

A method and system for analyzing patterns in the relationships of notes of an input piece of music. The method comprises generating a set of the most frequently occurring note pitches in ascending pitch order that matches an interval pattern, and detecting out-of-key pitches that lie outside of this interval pattern. One or more potential key sequence bifurcations are identified which represent a list of possible key sequences according to forwards and backwards analysis. By finding patterns of repetition in the chordal sequences that may be generated according to these key sequence bifurcations, a key sequence that allows the most frequently recurring chord sequences may be chosen. Chord sequences may be analyzed by using ghost chords, temporary harmonic structures that are created, updated and finalized over time according to a combination of essential and inessential note fragments. The method further comprises identifying non-harmony pitches according to the analyzed chord sequence.