Development of the computer environment for the usage of online handwritten symbols

为了开发一个能够有效利用在线手写符号的系统，我研究了以下两个课题。首先，我提出了一种改进个人性格分类器的方法，该方法是通过使用特定用户写的在线字符合成的虚拟示例来改进从实例中学习的个人性格分类器。为了获得好的分类器，通常需要一个包含足够数量的手写字符变体的大型数据库。在本研究中，我提出了一种基于使用特定用户编写的在线字符的人工增强示例来训练支持向量机的字符识别方法。通过对每个笔画应用Sae变换，从在线字符合成虚拟示例。SVM分类器使用人工生成的模式进行训练。其次，为了方便初学者创作乐曲，本文提出了一种利用已有的音乐数据库扩充用户输入的乐曲的方法。程序概要如下：1。在数据库中，通过将用户输入的音乐与数据库中所有部分的音高序列进行比较，找到最相似的部分，2使用线性回归模型，计算检索到的音乐与用户输入的音乐之间的转换矩阵，3。利用计算出的矩阵对检索到的音乐前后的部分进行变换，可以产生新的音乐；生成的音乐被添加到用户输入音乐之前和之后的部件中。在我的实验中，我们使用一个包含12首音乐的数据库创作了几首曲子。结果证实，该工具可以产生舒适的音乐。

In order to develop a system in which online handwritten symbols can be utilized efficiently, I have studied the following two subjects. First I propose a method to improve the personal character classifiers which am learned from examples by using the virtual examples synthesized from on-line characters written by a particular user. To obtain the good classifiers, usually a large database which contains enough number of variations of handwritten characters is required. In this study, I have proposed a method to train SVM for character recognition based on the artificially augmented examples using on-line characters written by a particular user A virtual example is synthesized from an on-line character by applying Sae transformation to each stroke. SVM classifiers am trained by using the artificially generated patterns. The effectiveness of the proposed method was examined by experiments of handwritten Japanese Hiragana character classification Second, to make it easier for a novice composer to produce a piece of music, a method which expands a user-entered music using an existing music database, has been proposed. The outline of the procedure is as follows: 1. in the database, the most similar part is found by comparison between the urer-entered music and all parts of the database based on their pitch sequences, 2 using linear regression model, a transformation matrix between the retrieved music and the user-entered music, is calculated, 3. new music can be produced by applying the transformation with the calculated matrix to the parts before and after the retrieved music, and 4. the produced music am added to the parts before and after the user-entered music. In my experiments, we composed several Owes of music with the use of a database which consists of twelve pieces of music. As a result, it was confirmed that the tool could produce comfortable music.