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