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\maketitle
\begin{abstract}
A command-line tool is proposed for the exploration of a new form of audio
synthesis known as ``concatenative-synthesis'' (CS): A form of synthesis that uses
perceptual audio analyses to arrange small segments of audio based on their
characteristics. The tool is designed to synthesise representations of an
input sound using a database of source sounds. This involves the
segmentation and analysis of both the input sound and database, matching of
input segments to their closest segment from the database, and the
re-synthesis of the closest matches from the database to produce the final
result.\\
A command-line tool and Python framework is proposed for the exploration of
a new form of audio synthesis known as ``concatenative-synthesis'' (CS): A
form of synthesis that uses perceptual audio analyses to arrange small
segments of audio based on their characteristics. The tool is designed to
synthesise representations of an input sound using a database of source
sounds. This involves the segmentation and analysis of both the input sound
and database, matching of input segments to their closest segment from the
database, and the re-synthesis of the closest matches from the database to
produce the final result.\\
The aim was to produce a tool capable of generating high quality sonic
representations of an input, and to present a variety of examples that
demonstrated the breadth of possibilities that this style of synthesis has
to offer. There are a number of other projects that use this form of
synthesis, however this project aims primarily to explore the further
potential offered through the offline processing of large databases, of
which considerably less research exists.\\
to offer. There are a number of projects that use this form of synthesis,
however this project aims primarily to explore the further potential
offered through the offline processing of large databases.\\
Results demonstrate the wide variety of sounds that can be produced using
this method of synthesis. A number of technical issues are outlined that
@@ -94,7 +93,7 @@
then be used for grain selection in the process of synthesizing output for
a wide range of applications~\parencite[p.102]{Schwarz2007}.
\subsection*{Related Works}
\section*{Related Works}
A number of programs utilize CS to achieve various goals. The process has
been used for applications in areas such as Speech Synthesis, Instrument
synthesis and for applications in creative sound design.\\
@@ -107,7 +106,7 @@
using other synthetic methods for modeling an
instrument~\parencite[p.24]{Maestre2009a}.
\subsubsection*{Speech Synthesis}
\subsection*{Speech Synthesis}
Creating a natural and intelligible realisation is an important factor when
developing a speech synthesis system.*add part about continuity here* The
Talkapillar project is one such example of how highly convincing results
@@ -117,12 +116,11 @@
transformed to appear as if they were spoken by the voice in the
database.~\parencite{Hueber}
\subsubsection*{Instrument Synthesis}
\subsection*{Instrument Synthesis}
Progress has also been made in improving the quality of instrument
synthesis. As with speech synthesis, the use of samples directly allows for
natural sounding results, which provides a method for reproducing real
instruments convincingly.\\
Another important aspect of instrument synthesis is that of performer
instruments convincingly. Another important aspect of instrument synthesis is that of performer
expression. The reproduction of performance qualities such as dynamics,
timbre and timing are essential when emulating a real instrument and CS has
been used to effectively reproduce these aspects. This is achieved through
@@ -131,26 +129,26 @@
seamlessly from one articulation to the next, the CS software will join
grains to produce the varyation in articulations. This contrasts the
traditional approach to sampling, where samples are played in isolation,
resulting in a discontinuity between adjacent samples. The comercial
software synthesizer ``Synful'' (\url{www.synful.com}) successfully
demonstrates the use of CS to produce highly convincing recreations of
orchestral instrument performances in real-time.
~\parencite[p.82]{Lindemann2007}.
resulting in a discontinuity between adjacent samples~\parencite[p.82]{Lindemann2007}.
The Catapillar project is one such example of this use of CS.
By using a viterbi algorithm, the project is able to calculate the
smoothest overall transition between grains accross the output, resulting
in convincing synthesis of orchestral instrument performances~\parencite[p.5]{Schwarz2003}.
\subsubsection*{Creative Sound Design}
\subsection*{Creative Sound Design}
The flexibilty of CS allows for creativity in a broader context than simply
emulating real-world instruments and speech. It can also be used as a tool
to explore the possibilities for synthesizing new abstract sounds for
creative purposes.\\
A prominent project in this area of CS is IRCAM's CataRT project *needs
reference*. The project focuses on the playback of source grains based on
their proximity to a target in multi-dimensional descriptor space.
By providing a target point in the descriptor space, the user is able to
navigate the database, playing selections of samples that are nearest to
the target. This allows the user to explore the database intuitively
through a graphic user interface, selecting a point in 2-dimensional space
with the mouse. Grains are then played back in real-time to create an
``audio mosaic''.\\
A prominent project in this area of CS is IRCAM's CataRT
project~\parencite{Schwarz2006}. The project focuses on the playback of
source grains based on their proximity to a target in multi-dimensional
descriptor space. By providing a target point in the descriptor space, the
user is able to navigate the database, playing selections of samples that
are nearest to the target. This allows the user to explore the database
intuitively through a graphic user interface, selecting a point in
2-dimensional space with the mouse. Grains are then played back in
real-time to create an ``audio mosaic''.\\
Alternatively, target audio can be provided and analysed to create a target
location based on it's location in the descriptor space. Tremblay and
Schwarz's~\citeyearpar{Tremblay2010} use of CataRT to explore
@@ -164,12 +162,16 @@
guitar. The result is a performance that mixes characteristics of both the
bass guitar output and the qualities of the corpus database to create a
hybrid of the two.
\section*{Concatenator Program Design and Implementation}
Aims:
\section{Concatenator}
The concatenator project aims to provide a Python framework and
command-line tool for concatenative synthesis.
Why Python?
instrument resynthesis onto a pre-existing source sound, rather than from scratch onto things like midi notes.
Offline processing to allow for large databases to be used - disadvantage: loss of feedback between performer and system, as described in PA's paper.
advantage: Real-time approach results in reduced continuity of grains
\section*{Program Design and Implementation}
\subsection*{Framework Design}
\subsection*{Descriptor Implementation}
@@ -187,7 +189,7 @@
Spectral matching~\parencite{Hoffman2009}
Use of RPM?~\parencite[p.82]{Lindemann2007}
Viterbi path search~\parencite[p.1]{Schwarz2006a}
Viterbi path search~\parencite[p.1]{Schwarz2006}
\section*{Conclusion}