## 1 Introduction
Although there are significant works on robot-assisted handwriting, most of these works (e.g., [17; 19; 20; 22]) were performed with equipment that was not intended for natural HRI. A humanoid robot is considered more suitable, as it resembles the human appearance and, thus, can improve its integration within social contexts [2]. Within the context of humanoid robots, NAO is one of the most well-known robots used for HRI and certainly can perform writing tasks, as presented in [23]. However, its cost (approximately 8,000.00 USD as of 2014) makes it affordable just for some users with significant economic resources. On the other hand, the integration of robot-assisted handwriting within the educational context has not been explored in the literature. Nevertheless, the work presented in [4; 15] has studied this situation, presenting a \"learning by teaching\" paradigm to improve handwriting skills in children. The NAO robot was used to perform trajectories that were expected to represent handwritten Latin alphabet characters and single words with different variability levels. However, these characters were not actually \"written\" by the robot. Instead, these characters were displayed in a tablet, which was synchronized with the NAO's movements (robot trajectory was synchronized with the tablet trajectory display). The robot intentionally added variability to the trajectories while writing words observed in cards presented by the children. This variability represented typical mistakes of children learning handwriting. Then, children would evaluate the word written by the robot (displayed in the tablet) and present the correct (or most appropriate) writing. With this approach, children could improve their handwriting skills by teaching the robot the correct trajectories. An issue regarding the handwriting task presented in [4; 15] is that physical writing was not actually performed. While robot simulation is an attractive alternative for implementation, it is important to consider the practical conditions to achieve a reliable evaluation of the handwriting task. This is because elements of the real world, as the precision of the servomechanisms, texture of the writing plane and the type of pen, including the ink, affect the dynamics of the writing task. In comparison with the NAO robot, the Bioloid system is a more affordable equipment for real implementations due to its cost (1200.00 USD as of 2015). Although no work related to handwriting with this system has been found in the literature, it has been widely used for similar purposes. In [25], the Bioloid was used to build a robotic arm for the task of drawing faces. This work is important for the purpose of writing, because it presented the use of the Bioloid to draw visual patterns. An advantage of the Bioloid system is that it can be configured into different architectures, including the humanoid architecture. This paper is focused on providing the techniques and models to use the Bioloid system for handwriting of the Mexican Spanish language. Speech recognition is considered as the input channel for handwriting. It is expected that the resources presented in this paper can be used for the development of educational applications as those described in [2; 4]. The contributions of the present work are listed as follows:  
1. development of a physical speech transcription system by means of robot-assisted handwriting;
2. performance evaluation of the humanoid Bioloid to draw small (1.0 cm width) alphabet characters in curved lowercase format;
3. development of the kinematic models for the humanoid Bioloid to perform the drawing of the Mexican Spanish alphabet with both arms;
4. development of a two-arm writing scheme for the transcription (handwriting) of large spoken sentences (multiple words). This paper is structured as follows: In Section 2, an overview of the Bioloid system is presented. Then, in Section 3, the details of the speech-to-text transcriptor are presented.