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Loris for Your Cough
Roshan Mansinghani, Esmeralda Martinez, James McDougall, Travis McPhail
Goal:
Analyze the possibility of removing short-time noise, such as
coughs or sneezes, from live recorded audio files.
2.) Reassigned Bandwidth-Enhanced Method of Additive
Synthesis [Fitz]
•Implements MQ method.
•Differs in handling noise as to eliminate introduced errors:
•Short, “jittery” tracks can be considered noise.
•Removes short tracks while still conserving signal energy
and frequency centers.
Our Algorithm:
•Noise is represented by short duration tracks.
•If a track had large gaps (multiple windows) between partials
it was broken into smaller pieces.
•Each track was analyzed for duration.
•If a track’s duration was less than a threshold it was removed.
•The signal was reconstructed using standard MQ methods.
Spectrogram of clarinet and cough
Motivation:
Often during live recorded concerts people cough or sneeze.
This noise appears in the recording and stands out from the
surrounding music.
Partial tracks before filtering
Before and after removal of noise tracks [Fitz]
Approach:
•Record a simple audio file, such as a clarinet playing a
single note with a cough in the middle.
•Break the file up into short-time windows.
•Analyze the frequency content of each window separately
and remove unwanted noise.
•Reassemble the file with as little distortion to the music as
possible.
•Increases bandwidth of tracks in the vicinity of the
rejected track.
•Increases
bandwidth
using
Bandwidth-Enhanced
Oscillators.
Results:
Effect of Bandwidth-Enhanced Oscillator on a single frequency[Fitz]
Background:
1.) The McAulay and Quatieri (MQ) Method
•Window off overlapping sections of the signal.
•Compute Fourier Transform of each window and find
dominant frequencies (partials).
•Connect partials from each window to track their progression
through time.
Partial tracks after filtering
•The noise frequencies were completely removed
including the low frequency components.
•The low frequency, long lived tracks were preserved.
•Most of the upper harmonic information was also lost.
Implementation: Loris Sound Software
•A C++ library implementing the Bandwidth-Enhanced
Model.
•Handles windowing of signal using a Kaiser window.
Spectrogram of clarinet with cough removed
Future Research:
Magnitude of Kaiser WindowFrequency Response of
Kaiser Window
Figure 2 [Fitz]
•Interpolate between connected points to generate a smooth
track.
•Use the tracks to develop cosine terms with time-varying
amplitude, phase, and frequency.
•Re-assemble sound by summing cosine terms.
When re-assembling noisy signals articles are
introduced into the reconstructed signal.
Acknowledgements:
•Computes Short-time Fourier Transforms.
•Tracks the progression of Partials through time.
•Uses the reconstruction process defined in the MQ model.
•Graphical User Interface (Fossa) for viewing amplitude and
frequency tracks.
•Improved algorithm to not remove upper harmonics.
•Automated removal of noise.
•Use Loris sound morphing capabilities to morph two or
more sound files.
•Possible removal of other types of extraneous noise (cell
phone, keys, clapping, etc.)
Contact Information:
•Roshan Mansinghani: [email protected]
•Esmerelda Martinez: [email protected]
•James McDougall: [email protected]
•Travis McPhail: [email protected]
Frequency Track for a clarinet playing a single note.
Kelly Fitz, Lippold Haken, and other Cerl Sound Group Members. Susanne Lefver, developer of Fossa. Dr.Baraniuk.