A connectionist approach in music perception.
Little research has been carried out in order to understand the mechanisms underlying
the perception of polyphonic music. Perception of polyphonic music involves thematic
recognition, that is, recognition of instances of theme through polyphonic voices, whether
they appear unaccompanied, transposed, altered or not. There are many questions still
open to debate concerning thematic recognition in the polyphonic domain. One of them,
in particular, is the question of whether or not cognitive mechanisms of segmentation and
thematic reinforcement facilitate thematic recognition in polyphonic music.
This dissertation proposes a connectionist model to investigate the role of segmentation
and thematic reinforcement in thematic recognition in polyphonic music. The model
comprises two stages. The first stage consists of a supervised artificial neural model to
segment musical pieces in accordance with three cases of rhythmic segmentation. The
supervised model is trained and tested on sets of contrived patterns, and successfully
applied to six musical pieces from J. S. Bach. The second stage consists of an original
unsupervised artificial neural model to perform thematic recognition. The unsupervised
model is trained and assessed on a four-part fugue from J. S. Bach.
The research carried out in this dissertation contributes into two distinct fields. Firstly,
it contributes to the field of artificial neural networks. The original unsupervised model
encodes and manipulates context information effectively, and that enables it to perform sequence
classification and discrimination efficiently. It has application in cognitive domains
which demand classifying either a set of sequences of vectors in time or sub-sequences
within a unique and large sequence of vectors in time. Secondly, the research contributes
to the field of music perception. The results obtained by the connectionist model suggest,
along with other important conclusions, that thematic recognition in polyphony is not
facilitated by segmentation, but otherwise, facilitated by thematic reinforcement.