Microsoft Technology Licensing, LLC

Ian Simon

Sumit Basu

Dan Morris

David Nister

Kazuhito Koishida

Maneesh Agrawala

Chad Gibson

David H Salesin

Adil Ahmed Sherwani

Tom Butcher

Various embodiments enable audio data, such as music data, to be captured, by a device, from a background environment and processed to formulate a query that can then be transmitted to a content recognition service. In one or more embodiments, multiple queries are transmitted to the content recognition service. In at least some embodiments, subsequent queries can progressively incorporate previous queries plus additional data that is captured. In one or more embodiments, responsive to receiving the query, the content recognition service can employ a multi-stage matching technique to identify content items responding to the query. This matching technique can be employed as queries are progressively received.

Query and matching for content recognition

A graphical user interface for facilitating generation of an accompaniment for a recorded audio melody is described. A Hidden Markov Model, trained with blended chord transition matrices and melody observation matrices, is used for providing the accompaniment for the recorded audio melody. The recorded audio melody includes segments. Frequency analysis of the recorded audio melody is performed. The total duration of each fundamental frequency within a segment of the melody is summed. Based on the summing, a probability for each possible chord for each segment is computed. Based on the computed probabilities, a set of chords are selected for the segments. The chords are displayed on a chord chart of the graphical user interface. The graphical user interface facilitates various manipulations using the chords and/or controls, and generation of a new accompaniment for a recorded audio melody based on the manipulations.

Automatic accompaniment for vocal melodies

A 'Concatenative Synthesizer' applies concatenative synthesis to create a musical output from a database of musical notes and an input musical score (such as a MIDI score or other computer readable musical score format). In various embodiments, the musical output is either a music score, or an analog or digital audio file. This musical output is constructed by evaluating the database of musical notes to identify sets of candidate notes for each note of the input musical score. An 'optimal path' through candidate notes is identified by minimizing an overall cost function through the candidate notes relative to the input musical score. The musical output is then constructed by concatenating the selected candidate notes. In further embodiments, the database of musical notes is generated from any desired musical genre, performer, performance, or instrument. Furthermore, notes in the database may be modified to better fit notes of the input musical score.

Creating music via concatenative synthesis

A method for generating an accompaniment for a recorded audio melody includes providing a recorded audio melody that includes segments; performing a frequency analysis of the recorded audio melody; summing the total duration of each fundamental frequency within a segment of the melody; based on the summing, computing a probability for each possible chord for each segment; based on the computed probabilities, selecting a set of chords for the segments; and outputting the set of chords as an accompaniment for the recorded audio melody. Various other methods, devices, systems, etc. are also disclosed.

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Ian Simon