Acoustic impulse response prediction using regularized regression models
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Typ
Examensarbete för masterexamen
Program
Sound and vibration (MPSOV), MSc
Publicerad
2021
Författare
Karin, Hulling
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Different methods of calculating the impulse response of rooms have been developed
over the years and is an important measure within e.g. room acoustics and building
acoustics. In this thesis work, two different regularized regression models were
evaluated to see if it is possible to estimate the rooms’ impulse response simply by
knowing some features of the room. This way, the room impulse response would be
obtained in a much more simple and straightforward way compared to the already
existing methods.
The two models that were evaluated in this thesis work are called LASSO (Least
Absolute Shrinkage and Selection Operator) and ridge regression, these models both
generate a weight vector, given a training set and a target. Considering a large data
set of different room properties as the training set, the target describes a new set of
room properties. The aim was to be able to describe the target as the superposition
of the training set multiplied with the weight vector, generated by the models. This
weight vector was then tested to see if the relationship also could be applied to the
impulse responses, by the superposition of the impulse responses in the training set
multiplied with the same weight vector.
One difference between the two models is that the LASSO model can shrink the coefficients
belonging to the less important features to zero, while for ridge regression,
the coefficients can only get close to zero. This is what encourages sparsity in the
LASSO model, which turned out to be a winning concept.
Results showed that the LASSO model estimated room impulse responses around
20 dB better than the ridge regression model. The results also show that there is
potential for these models with some adjustments within the model, but also by
weighing the features in order of importance.
Beskrivning
Ämne/nyckelord
Room impulse response, LASSO, ridge regression, acoustics , regression models, MCRoomSim, pyroomacoustics, sparse representation