Statistical Language Models for On-line Handwritten Sentence Recognition

International audienceThis paper investigates the integration of a statistical language model into an on-line recognition system in order to improve word recognition in the context of handwritten sentences. Two kinds of models have been considered: n-gram and n-class models (with a statistical approach to create word classes). All these models are trained over the Susanne corpus and experiments are carried out on sentences from this corpus which were written by several writers. The use of a statistical language model is shown to improve the word recognition rate and the relative impact of the different language models is compared. Furthermore, we illustrate the interest to define an optimal cooperation between the language model and the recognition system to re-enforce the accuracy of the system

A Priori and A Posteriori Integration and Combination of Language Models in an On-line Handwritten Sentence Recognition System

International audienceThis paper investigates the integration of different language models into an on-line sentence recognition system. The impact of n-gram and n-class (based on statistically and on morpho-syntactically classes) models, built on the Brown corpus, is compared in terms of word recognition rate. Furthermore, their integration in different steps of the recognition process (during it or to rescore the Nbest list of proposed sentences) is considered, thus showing better performances when used the sooner. Combinations of these models are also studied, in addition to the integration in the aforementioned recognition steps. All experiments are carried out on sentences from the Brown corpus which were written by several writers

A Proposal for Processing and Fusioning Multiple Information Sources in Multimodal Dialog Systems

Proceedings of: PAAMS 2014 International Workshops. Agent-based Approaches for the Transportation Modelling and Optimisation (AATMO' 14 ) & Intelligent Systems for Context-based Information Fusion (ISCIF' 14). Salamanca, Spain, June 4-6, 2014.Multimodal dialog systems can be defined as computer systems that process two or more user input modes and combine them with multimedia system output. This paper is focused on the multimodal input, providing a proposal to process and fusion the multiple input modalities in the dialog manager of the system, so that a single combined input is used to select the next system action. We describe an application of our technique to build multimodal systems that process user's spoken utterances, tactile and keyboard inputs, and information related to the context of the interaction. This information is divided in our proposal into external and internal context, user's internal, represented in our contribution by the detection of their intention during the dialog and their emotional state.This work was supported in part by Projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485)

A Review of Verbal and Non-Verbal Human-Robot Interactive Communication

In this paper, an overview of human-robot interactive communication is presented, covering verbal as well as non-verbal aspects of human-robot interaction. Following a historical introduction, and motivation towards fluid human-robot communication, ten desiderata are proposed, which provide an organizational axis both of recent as well as of future research on human-robot communication. Then, the ten desiderata are examined in detail, culminating to a unifying discussion, and a forward-looking conclusion

A step towards understanding paper documents

This report focuses on analysis steps necessary for a paper document processing. It is divided in three major parts: a document image preprocessing, a knowledge-based geometric classification of the image, and a expectation-driven text recognition. It first illustrates the several low level image processing procedures providing the physical document structure of a scanned document image. Furthermore, it describes a knowledge-based approach, developed for the identification of logical objects (e.g., sender or the footnote of a letter) in a document image. The logical identifiers provide a context-restricted consideration of the containing text. While using specific logical dictionaries, a expectation-driven text recognition is possible to identify text parts of specific interest. The system has been implemented for the analysis of single-sided business letters in Common Lisp on a SUN 3/60 Workstation. It is running for a large population of different letters. The report also illustrates and discusses examples of typical results obtained by the system

Character Recognition

Character recognition is one of the pattern recognition technologies that are most widely used in practical applications. This book presents recent advances that are relevant to character recognition, from technical topics such as image processing, feature extraction or classification, to new applications including human-computer interfaces. The goal of this book is to provide a reference source for academic research and for professionals working in the character recognition field

A Clinical study on the Efficacy of Homoeopathic Management of Dysgraphia in School Going Children

AIM OF THE STUDY: To study the efficacy of homoeopathic management of dysgraphia in school going children. MATERIALS AND METHODS: In order to achieve the aims and objectives, the study was done in a systematic way. Students were examined and screened from the School Heath Programs conducted different schools of Kanyakumari district using Colorado Learning Disability Questionnaire. From the initial screening students found to be having risk of Dysgraphia was directed to the next level of screening with LEARNING DISABILITY DIAGNOSTIC INVENTORY TOOL and classified them as Likely, Possibly and Unlikely of Dysgraphia. Then the dysgraphic students were subjected to find their I.Q quotient by WESCHLERS IQ TEST. Cases were randomly selected by the Random Sampling Technique as per the inclusion and exclusion criteria. Data collected were recorded in the pre-structured SKHMC standardized case record. Case details were done according to the rule of ideal homoeopathic cure followed by case analysis and the totality were constructed. Prescription were done with due reference to Repertory, Materia Medica and Organon of Medicine. Potency selection and repetition were done according to the demand of each case. Every case were assessed at regular intervals and were followed for 6 months to one year. Improvement assessment of each case were done by L.D.D.I tool during the follow up after 6months to one year. Over all general well being of the patient were also assessed. STUDY OUTCOME: After the assessment of study, majority of patients belonged to age groups of 8 – 10 years 16 (53%) and 11 – 13 years 11(37%), with males 21(70%) and females 9 (30%) respectively. Also male age group of 8 – 10 years stood predominantly with 13(43%) and female age group 8 – 10 years 3 (10%). The students with Grade 3 of 11 (37%) patients and Grade 4 of 13(43%) patients had higher possibility to have writing disability and 6 (20%) patients under Grade 5. Medicines seen to be more effective were Lycopodium, Natrum Mur, Calcarea–carb, Silicea, Phosphorus etc. Most of the cases diagnosed along with Dysgraphia were with ADHD, ADD, ODD, CD or DBD. Majority of students, 12 (40%) each showed moderate and mild improvement with 6(20%) good improvement in the writing scores. CONCLUSION: Therefore, Homoeopathy is effective in managing Dysgraphia in school going children. The study of the efficacy of homoeopathic management of Dysgraphia in school going children was based on the comparison of before and after treatment of writing scores of LDDI