## 3 Speech-to-Text Transcriptor
### Speech Recognizer and Alphabet Segmentation  
The automatic speech recognizer (ASR system) used in this work is a modification of the base system presented in [30] for Mexican Spanish. The base system enables the user to perform the continuous entry of new words and dynamic speaker adaptation. It can recognize isolated words and sentences with an overall recognition accuracy for male and female speakers over 90% with a vocabulary of less than 500 words [30]. The recognition engine was developed with HTK (Version 3.4) [31], and the acoustic modeling was performed at the phonetic level with the set of phonemes defined in [32]. In Figure 3, the graphical user interface (GUI) of the speech-to-text transcript is presented. The interface itself integrates the speech recognizer and the alphabet transcript for the decoded speech. The GUI was programmed with the GUIDE toolkit of MATLAB. Figure 3: Main interface of the speech-to-text transcript. Figure 2: Modules of the speech-to-text transcript. From Figure 3, the button labeled _\"Registro y Adaptacion de Usuario\"_ (User Registration and Adaptation) leads to another interface that enables the user to adapt the speech recognizer to his/her voice patterns. This interface is presented in Figure 4 and includes fields to add a new user's name (_\"Escriba Nombre de Usuario\"_) or select an already registered user (_\"Seleccione Usuario\"_). As the new user is added, or a previously-registered user is selected, he/she can proceed to perform the speaker adaptation process. For this purpose, the user must record 16 sentences. This is done by pressing the button labeled with the associated sentence (e.g., _\"MI FAMILIA VIVIO EN MEXICO\"_). By doing this, the user provides speech samples for the adaptation process, which is realized and finalized by pressing the button _\"Adaptar\"_ (to adapt). More details of this interface can be found in [30]. The button labeled _\"Reconocord y Transcriptor de Voz\"_ (Speech Recognizer and Transcriptor) leads to the interface of the speech-to-text transcriptor. This interface is presented in Figure 5. The first step to use this interface is to select an already registered user by using the pop-up menu _\"Seleccione Usuario\"_. Then, the user can proceed to either add new vocabulary by writing it down in the field _\"Anadir Nuevas Frases o Palabras\"_ or use the recognizer. If new vocabulary is added, the user can use this vocabulary as stimuli to perform additional speaker adaptation: the user records the pronunciation of the added sentence by pressing _\"Grabar para Adaptacion\"_ and then, by pressing the _\"OK\"_ button, the interface realizes and finishes the process. The additional vocabulary is updated into the ASR system by pressing the _\"Crea Modelo de Lenguaje\"_ button. If the user wants to use the recognizer, he/she must first define an adjustment value for the recognizer under _\"Valor de Ajuste (1-30):\"_. This value represents the scale grammar factor and controls the influence of the language model (statistical information of the vocabulary) on the recognition process [30; 31]. Then, by pressing  
Figure 4: Speech adaptation interface of the speech-to-text transcriptor. \"_Ejecuta Reconocordor_\", the recording of the user's speech is started. When the user has finished this step, he/she just needs to press the button again. By doing this, the ASR starts the decoding process, and the recognized speech is displayed under the field \"_Frase Reconocida_\" (Recognized Sentence). In order to perform the transcription with the Bioloid robot (e.g., robot-assisted handwriting), the user just has to press the button \"_Transcripcion de Frase_\" (Transcription of Sentence). Internally, the interface performs a direct alphabet segmentation from uppercase to lowercase format of the words' alphabet characters displayed under \"_Frase Reconocida_\" (e.g., \"LA_MANANA_ES_FRIA\" _\"la manana es fria_\"). The symbol \"_\" is considered as an \"empty\" (space) alphabet character.