This release comes with a number of packaging and distribution improvements. The build system has received minor fixes and configurability enhancements. There are improved demonstration programs and improved UTF-8 support. Distributed text resources used to generate sample statistical data are now UTF-8 encoded. There are a few bugfixes and documentation updates.
A new statistical predictive plugin, based on recency promotion, is now available. There is a new simple GUI demonstration program, Prompter. Prompter is a soothsayer-enabled text editor that displays predictions generated by soothsayer through a pop-up autocompletion list. Native Windows support has been added via the MinGW/MSYS platform. There are enhancements to the build system and a number of bugfixes.
This release includes a number of under-the-hood changes. The focus has been on refactoring, restructuring, and cleaning up rather than adding new functionality. The source directory layout was changed to better reflect the logical structure. Improvements were made to the configuration system and the logging subsystem, which underwent a complete overhaul and rewrite. Man pages for the tools and demo programs are included.
このリリースでは、Pythonアプリケーションをネイティブに占い師に呼び出すことができます新しいPythonバインディングモジュールが含まれます。これはSolaris 10に移植されているとSun Studio 10と11のコンパイラでビルドされた。これはバグの修正および改善システムを構築しています。ライブラリの依存関係がクリーンアップされている。共有ライブラリがサポートするすべてのプラットフォーム上でWindowsを含む組み込まれている/ Cygwinの対象とする。
タグ:
Major feature enhancements
This release includes a new Python binding module, which enables Python applications to natively call into soothsayer. It has been ported to Solaris 10, and built with Sun Studio 10 and 11 compilers. It includes bugfixes and improvements to the build system. Library dependencies have been cleaned up. Shared libraries are now built on all supported platforms, including Windows/Cygwin targets.
The new generalized smoothed n-gram statistical
predictive plugin is included, which supports
arbitrary order n-grams. Used in combination with
the text2ngram tool, statistical predictions can
be generated by n-gram language models of
arbitrary cardinality. It uses an improved
heuristic to generate initial completion
candidates, by using highest order n-gram
statistics. This release includes notable bugfixes
and improvements to soothsayer simulator. A bug in
the simulator caused the reported Key Stroke
Reduction rate to be much lower than the actual
KSR achieved by soothsayer.
