12 research outputs found
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Automatic transcription of pitched and unpitched sounds from polyphonic music
Automatic transcription of polyphonic music has been an active research field for several years and is considered by many to be a key enabling technology in music signal processing. However, current transcription approaches either focus on detecting pitched sounds (from pitched musical instruments) or on detecting unpitched sounds (from drum kits). In this paper, we propose a method that jointly transcribes pitched and unpitched sounds from polyphonic music recordings. The proposed model extends the probabilistic latent component analysis algorithm and supports the detection of pitched sounds from multiple instruments as well as the detection of unpitched sounds from drum kit components, including bass drums, snare drums, cymbals, hi-hats, and toms. Our experiments based on polyphonic Western music containing both pitched and unpitched instruments led to very encouraging results in multi-pitch detection and drum transcription tasks
AUTOMATIC TRANSCRIPTION OF PITCHED AND UNPITCHED SOUNDS FROM POLYPHONIC MUSIC
codedemo: http://code.soundsoftware.ac.uk/projects/pu_amt
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Pitch shifting techniques for high-frequency passive sonar audio
Listening to passive sonar signals is a vital tool for sonar operators to classify underwater sound sources. While many passive sonar systems operate in the human auditory range (20 Hz to 20 kHz) there are a considerable number of high-frequency systems that extend beyond this range. This report examines pitch shifting algorithms for compressing ultrasonic, bandlimited passive sonar signals down into the auditory spectrum. By utilizing pitch shifting techniques the signal’s harmonic structure and length in time are retained. The frequency spectrum is lowered into the auditory range so that the sonar operator may then listen and characterize targets. Three pitch shifting algorithms are examined: Waveform Similarity Overlap-Add (WSOLA), Phase Vocoder, and Constant-Q Transform (CQT). Both synthetic and real sonar data is experimentally applied to each method and results are presented. Comparisons of performance are provided with an emphasis on feasibility for real-time sonar system implementation.Electrical and Computer Engineerin
Algorithms for the Construction of Incoherent Frames Under Various Design Constraints
Unit norm finite frames are generalizations of orthonormal bases with many
applications in signal processing. An important property of a frame is its
coherence, a measure of how close any two vectors of the frame are to each
other. Low coherence frames are useful in compressed sensing applications. When
used as measurement matrices, they successfully recover highly sparse solutions
to linear inverse problems. This paper describes algorithms for the design of
various low coherence frame types: real, complex, unital (constant magnitude)
complex, sparse real and complex, nonnegative real and complex, and harmonic
(selection of rows from Fourier matrices). The proposed methods are based on
solving a sequence of convex optimization problems that update each vector of
the frame. This update reduces the coherence with the other frame vectors,
while other constraints on its entries are also imposed. Numerical experiments
show the effectiveness of the methods compared to the Welch bound, as well as
other competing algorithms, in compressed sensing applications