Recognizer characterisation for combining handwriting recognition results at word level

2002 ◽  
Author(s):  
R.K. Powalka ◽  
N. Sherkat ◽  
R.J. Whitrow
Keyword(s):  
Handwriting Recognition ◽  
Word Level

ANALOGIC PREPROCESSING AND SEGMENTATION ALGORITHMS FOR OFFLINE HANDWRITING RECOGNITION

2003 ◽  
Vol 12 (06) ◽  
pp. 783-804 ◽  
Author(s):  
GERGELY TÍMÁR ◽  
KRISTÓF KARACS ◽  
CSABA REKECZKY
Keyword(s):  
Future Development ◽  
Handwriting Recognition ◽  
Iterative Algorithms ◽  
Front Propagation ◽  
Word Segmentation ◽  
Word Level ◽  
Segmentation Algorithms ◽  
Wave Front Propagation ◽  
Offline Handwriting Recognition ◽  
Dynamic Wave

This report describes analogic algorithms used in the preprocessing and segmentation phase of offline handwriting recognition tasks. A segmentation-based handwriting recognition approach is discussed, i.e., the system attempts to segment the words into their constituent letters. In order to improve their speed, the utilized CNN algorithms, whenever possible, use dynamic, wave front propagation-based methods instead of relying on morphologic operators were embedded into iterative algorithms. The system first locates the handwritten lines in the page image, then corrects their skew as necessary. It then searches for the words within the lines and corrects the skew at the word level as well. A novel trigger wave-based word segmentation algorithm is presented, which operates on the skeletons of words. Sample results of experiments conducted on a database of 25 handwritten pages along with suggestions for future development are presented.

scholarly journals LeRec: A NN/HMM Hybrid for On-Line Handwriting Recognition

1995 ◽  
Vol 7 (6) ◽  
pp. 1289-1303 ◽  
Author(s):  
Yoshua Bengio ◽  
Yann LeCun ◽  
Craig Nohl ◽  
Chris Burges
Keyword(s):  
Markov Model ◽  
Hidden Markov ◽  
Handwriting Recognition ◽  
Entire System ◽  
New Approach ◽  
Word Structure ◽  
Word Level ◽  
The Em Algorithm ◽  
Network Output ◽  
On Line

We introduce a new approach for on-line recognition of handwritten words written in unconstrained mixed style. The preprocessor performs a word-level normalization by fitting a model of the word structure using the EM algorithm. Words are then coded into low resolution "annotated images" where each pixel contains information about trajectory direction and curvature. The recognizer is a convolution network that can be spatially replicated. From the network output, a hidden Markov model produces word scores. The entire system is globally trained to minimize word-level errors.

MULTIMODAL COMPUTER-ASSISTED TRANSCRIPTION OF TEXT IMAGES AT CHARACTER-LEVEL INTERACTION

2012 ◽  
Vol 26 (05) ◽  
pp. 1263003 ◽  
Author(s):  
DANIEL MARTÍN-ALBO ◽  
VERÓNICA ROMERO ◽  
ALEJANDRO H. TOSELLI ◽  
ENRIQUE VIDAL
Keyword(s):  
Handwriting Recognition ◽  
Multimodal Interaction ◽  
Computer Assisted ◽  
Interactive Approach ◽  
Fine Grained ◽  
Word Level ◽  
User Acceptability ◽  
Whole Word ◽  
Decoding Accuracy ◽  
Text Images

Currently, automatic handwriting recognition systems are ineffectual in unconstrained handwriting documents. Therefore, to obtain perfect transcriptions, heavy human intervention is required to validate and correct the results of such systems. Given that this post-editing process is inefficient and uncomfortable, a multimodal interactive approach has been proposed in previous works, which aims at obtaining correct transcriptions with the minimum human effort. In this approach, the user interacts with the system by means of an e-pen and/or more traditional methods such as keyboard or mouse. This user's feedback allows to improve system accuracy and multimodality increases system ergonomics and user acceptability. Until now, multimodal interaction has been considered only at whole-word level. In this work, multimodal interaction at character-level is studied, that may lead to more effective interactivity, since it is faster and easier to write only one character rather than a whole word. Here we study this kind of fine-grained multimodal interaction and present developments that allow taking advantage of interaction-derived context to significantly improve feedback decoding accuracy. Empirical tests on three cursive handwritten tasks suggest that, despite losing the deterministic accuracy of traditional peripherals, this approach can save significant amounts of user effort with respect to fully manual transcription as well as to noninteractive post-editing correction.

Write, Attend and Spell

2021 ◽  
Vol 5 (3) ◽  
pp. 1-25
Author(s):  
Qian Zhang ◽  
Dong Wang ◽  
Run Zhao ◽  
Yinggang Yu ◽  
JiaZhen Jing
Keyword(s):  
Handwriting Recognition ◽  
Letter Recognition ◽  
Motion Sensors ◽  
Text Entry ◽  
Task Sequence ◽  
Convolutional Network ◽  
Word Level ◽  
Motion Features ◽  
Natural Solution ◽  
Small Form Factor

Text entry on a smartwatch is challenging due to its small form factor. Handwriting recognition using the built-in sensors of the watch (motion sensors, microphones, etc.) provides an efficient and natural solution to deal with this issue. However, prior works mainly focus on individual letter recognition rather than word recognition. Therefore, they need users to pause between adjacent letters for segmentation, which is counter-intuitive and significantly decreases the input speed. In this paper, we present 'Write, Attend and Spell' (WriteAS), a word-level text-entry system which enables free-style handwriting recognition using the motion signals of the smartwatch. First, we design a multimodal convolutional neural network (CNN) to abstract motion features across modalities. After that, a stacked dilated convolutional network with an encoder-decoder network is applied to get around letter segmentation and output words in an end-to-end way. More importantly, we leverage a multi-task sequence learning method to enable handwriting recognition in a streaming way. We construct the first sequence-to-sequence handwriting dataset using smartwatch. WriteAS can yield 9.3% character error rate (CER) on 250 words for new users and 3.8% CER for words unseen in the training set. In addition, WriteAS can handle various writing conditions very well. Given the promising performance, we envision that WriteAS can be a fast and accurate input tool for smartwatch.

Collecting Words: A Clinical Example of a Morphology-Focused Orthographic Intervention

2020 ◽  
Vol 51 (3) ◽  
pp. 544-560 ◽  
Author(s):  
Kimberly A. Murphy ◽  
Emily A. Diehm
Keyword(s):  
Written Language ◽  
Morphological Knowledge ◽  
English Orthography ◽  
Word Level ◽  
Novel Approach ◽  
Language Pathology ◽  
The One ◽  
Critical Intervention ◽  
Reading And Spelling ◽  
Reading And Spelling Difficulties

Purpose Morphological interventions promote gains in morphological knowledge and in other oral and written language skills (e.g., phonological awareness, vocabulary, reading, and spelling), yet we have a limited understanding of critical intervention features. In this clinical focus article, we describe a relatively novel approach to teaching morphology that considers its role as the key organizing principle of English orthography. We also present a clinical example of such an intervention delivered during a summer camp at a university speech and hearing clinic. Method Graduate speech-language pathology students provided a 6-week morphology-focused orthographic intervention to children in first through fourth grade ( n = 10) who demonstrated word-level reading and spelling difficulties. The intervention focused children's attention on morphological families, teaching how morphology is interrelated with phonology and etymology in English orthography. Results Comparing pre- and posttest scores, children demonstrated improvement in reading and/or spelling abilities, with the largest gains observed in spelling affixes within polymorphemic words. Children and their caregivers reacted positively to the intervention. Therefore, data from the camp offer preliminary support for teaching morphology within the context of written words, and the intervention appears to be a feasible approach for simultaneously increasing morphological knowledge, reading, and spelling. Conclusion Children with word-level reading and spelling difficulties may benefit from a morphology-focused orthographic intervention, such as the one described here. Research on the approach is warranted, and clinicians are encouraged to explore its possible effectiveness in their practice. Supplemental Material https://doi.org/10.23641/asha.12290687

Factors Influencing Cognate Performance for Young Multilingual Children's Vocabulary: A Research Synthesis

2020 ◽  
Vol 29 (4) ◽  
pp. 2170-2188
Author(s):  
Lindsey R. Squires ◽  
Sara J. Ohlfest ◽  
Kristen E. Santoro ◽  
Jennifer L. Roberts
Keyword(s):  
Test Validity ◽  
Reaction Times ◽  
Bilingual Children ◽  
Second Grade ◽  
High Quality Research ◽  
Word Level ◽  
Research Questions ◽  
Word Characteristics ◽  
Study Inclusion ◽  
Task Level

Purpose The purpose of this systematic review was to determine evidence of a cognate effect for young multilingual children (ages 3;0–8;11 [years;months], preschool to second grade) in terms of task-level and child-level factors that may influence cognate performance. Cognates are pairs of vocabulary words that share meaning with similar phonology and/or orthography in more than one language, such as rose – rosa (English–Spanish) or carrot – carotte (English–French). Despite the cognate advantage noted with older bilingual children and bilingual adults, there has been no systematic examination of the cognate research in young multilingual children. Method We conducted searches of multiple electronic databases and hand-searched article bibliographies for studies that examined young multilingual children's performance with cognates based on study inclusion criteria aligned to the research questions. Results The review yielded 16 articles. The majority of the studies (12/16, 75%) demonstrated a positive cognate effect for young multilingual children (measured in higher accuracy, faster reaction times, and doublet translation equivalents on cognates as compared to noncognates). However, not all bilingual children demonstrated a cognate effect. Both task-level factors (cognate definition, type of cognate task, word characteristics) and child-level factors (level of bilingualism, age) appear to influence young bilingual children's performance on cognates. Conclusions Contrary to early 1990s research, current researchers suggest that even young multilingual children may demonstrate sensitivity to cognate vocabulary words. Given the limits in study quality, more high-quality research is needed, particularly to address test validity in cognate assessments, to develop appropriate cognate definitions for children, and to refine word-level features. Only one study included a brief instruction prior to assessment, warranting cognate treatment studies as an area of future need. Supplemental Material https://doi.org/10.23641/asha.12753179

Morphological Awareness Skills of Second- and Third-Grade Students With and Without Speech Sound Disorders

2020 ◽  
Vol 51 (3) ◽  
pp. 603-616
Author(s):  
Kenn Apel ◽  
Victoria S. Henbest
Keyword(s):  
Word Reading ◽  
Speech Sound ◽  
Morphological Awareness ◽  
Literacy Skills ◽  
Receptive Vocabulary ◽  
Real Word ◽  
Speech Sound Disorders ◽  
Word Level ◽  
Third Grade Students ◽  
Pseudoword Reading

Purpose Morphological awareness is the ability to consciously manipulate the smallest units of meaning in language. Morphological awareness contributes to success with literacy skills for children with typical language and those with language impairment. However, little research has focused on the morphological awareness skills of children with speech sound disorders (SSD), who may be at risk for literacy impairments. No researcher has examined the morphological awareness skills of children with SSD and compared their skills to children with typical speech using tasks representing a comprehensive definition of morphological awareness, which was the main purpose of this study. Method Thirty second- and third-grade students with SSD and 30 with typical speech skills, matched on age and receptive vocabulary, completed four morphological awareness tasks and measures of receptive vocabulary, real-word reading, pseudoword reading, and word-level spelling. Results Results indicated there was no difference between the morphological awareness skills of students with and without SSD. Although morphological awareness was moderately to strongly related to the students' literacy skills, performance on the morphological awareness tasks contributed little to no additional variance to the children's real-word reading and spelling skills beyond what was accounted for by pseudoword reading. Conclusions Findings suggest that early elementary-age students with SSD may not present with concomitant morphological awareness difficulties and that the morphological awareness skills of these students may not play a unique role in their word-level literacy skills. Limitations and suggestions for future research on the morphological awareness skills of children with SSD are discussed.

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