Reading and embodying the script during the theatrical rehearsal

The paper develops an ethnomethodological, conversation-analytic and multimodal approach of the theatrical rehearsal, examining how participants collaboratively read, understand and embody the script. After examining the spatial organization of the setting, the paper focuses on the following interactional practices: (1) from the participants’ perspective, the script appears as a written sequence of lines to connect with their knowledge of social interaction; (2) participants understand the script through their sequential and contextual readings; (3) they collaboratively connect the utterance of written lines with embodied behavior through the check-reading, and (4) by coordinating the lines with pauses and gaze directions. The analysis relies on video-recordings in French and Japanese collected at an Art center in Japan.

The A2iA Intercheque System: Courtesy Amount and Legal Amount Recognition for French Checks

We developed a check reading system, termed INTERCHEQUE, which recognizes both the legal (LAR) and the courtesy amount (CAR) on bank checks. The version presented here is designed for the recognition of French, omni-bank, omni-scriptor, handwritten bank checks, and meets industrial requirements, such as high processing speed, robustness, and extremely low error rates. We give an overview of our recognition system and discuss some of the pattern recognition techniques used. We also describe an installation which processes of the order of 70,000 checks per day. Results on a data base of about 170,000 checks show a recognition rate of about 75% for an error rate of the order of 1/10,000 checks.

Check Amount Recognition Based on the Cross Validation of Courtesy and Legal Amount Fields

Check amount recognition is one of the most promising commercial applications of handwriting recognition. This paper is devoted to the description of the check reading system developed to recognize amounts on American personal checks. Special attention is paid to a reliable procedure developed to reject doubtful answers. For this purpose the legal (worded) amount on a personal check is recognized along with the courtesy (digit) amount. For both courtesy and legal amount fields, a brief description of all recognition stages beginning with field extraction and ending with the recognition itself are presented. We also present the explanation of problems existing at each stage and their possible solutions. The numeral recognizer used to read the amounts written in figures is described. This recognizer is based on the procedure of matching input subgraphs to graphs of symbol prototypes. Main principles of the handwriting recognizer used to read amounts written in words are explained. The recognizer is based on the idea of describing the handwriting with the most stable handwriting elements. The concept of the optimal confidence level of the recognition answer is introduced. It is shown that the conditional probability of the answer correctness is an optimal confidence level function. The algorithms of the optimal confidence level estimation for some special cases are described. The sophisticated algorithm of cross validation between legal and courtesy amount recognition results based on the optimal confidence level approach is proposed. Experimental results on real checks are presented. The recognition rate at 1% error rate is 67%. The recognition rate without reject is 85%. Significant improvement is achieved due to legal amount processing in spite of a relatively low recognition rate for this field.