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Multimodal Interactive Pattern Recognition and Applications / by Alejandro Héctor Toselli, Enrique Vidal, Francisco Casacuberta
Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: SpringerLink BücherPublisher: London : Springer-Verlag London Limited, 2011Description: Online-Ressource (XVI, 274p. 86 illus., 52 illus. in color, digital)ISBN:- 9780857294791
- 005.437
- 4.019
- 006.4
- QA76.9.U83 QA76.9.H85
- TK7882.P3
Contents:
Summary: Many real-world applications of pattern recognition (PR) systems require human post-processing to correct the errors committed by machines. This can create bottlenecks in recognition systems, yielding high operational costs. This important text/reference proposes a radically different approach to this problem, in which users of a system are involved during the recognition process. This can help to avoid later errors and reduce the costs associated with post-processing. The book also examines a range of advanced multimodal interactions between the machine and the users, including handwriting, speech and gestures. Topics and features: presents a thorough introduction to the fundamental concepts and general PR approaches for multimodal interaction modelling and search (or inference), provides numerous examples and a helpful Glossary, includes work carried out in the context of the Spanish research program Multimodal Interaction in Pattern Recognition and Computer Vision (MIPRCV), which involves more than 100 highly-qualified researchers from ten research institutions, discusses approaches for computer-assisted transcription of handwritten and spoken documents, examines systems for computer-assisted language translation, interactive text generation and parsing, relevance-based image retrieval, and interactive document layout analysis, reviews several full working prototypes of multimodal interactive PR applications, including live demonstrations that can be publicly accessed through the Internet. Addressing the emerging field of interactive and multimodal systems in a fresh, unified and integrated way, this unique book is highly recommended reading for graduate students, academic and industrial researchers, lecturers, and practitioners working in the field of pattern recognition.PPN: PPN: 1650942664Package identifier: Produktsigel: ZDB-2-SCS
Multimodal Interactive Pattern Recognition and Applications; Foreword; Preface; Contents; Chapter 1: General Framework; 1.1 Introduction; 1.2 Classical Pattern Recognition Paradigm; 1.3 Interactive Pattern Recognition and Multimodal Interaction; 1.4 Interaction Protocols and Assessment; 1.5 IPR Search and Confidence Estimation; 1.6 Machine Learning Paradigms for IPR; References; Chapter 2: Computer Assisted Transcription: General Framework; 2.1 Introduction; 2.2 Common Statistical Framework for HTR and ASR; 2.3 Common Statistical Framework for CATTI and CATS; 2.4 Adapting the Language Model
2.5 Search and Decoding Methods2.6 Assessment Measures; References; Chapter 3: Computer Assisted Transcription of Text Images; 3.1 Computer Assisted Transcription of Text Images: CATTI; 3.2 CATTI Search Problem; 3.3 Increasing Interaction Ergonomics in CATTI: PA-CATTI; 3.4 Multimodal Computer Assisted Transcription of Text Images: MM-CATTI; 3.5 Non-interactive HTR Systems; 3.6 Tasks, Experiments and Results; 3.7 Conclusions; References; Chapter 4: Computer Assisted Transcription of Speech Signals; 4.1 Computer Assisted Transcription of Audio Streams; 4.2 Foundations of CATS
4.3 Introduction to Automatic Speech Recognition4.4 Search in CATS; 4.5 Word-Graph-Based CATS; 4.6 Experimental Results; 4.7 Multimodality in CATS; 4.8 Experimental Results; 4.9 Conclusions; References; Chapter 5: Active Interaction and Learning in Handwritten Text Transcription; 5.1 Introduction; 5.2 Confidence Measures; 5.3 Adaptation from Partially Supervised Transcriptions; 5.4 Active Interaction and Active Learning; 5.5 Balancing Error and Supervision Effort; 5.6 Experiments; 5.7 Conclusions; References; Chapter 6: Interactive Machine Translation; 6.1 Introduction
6.2 Interactive Machine Translation6.3 Search in Interactive Machine Translation; 6.4 Tasks, Experiments and Results; 6.5 Conclusions; References; Chapter 7: Multi-Modality for Interactive Machine Translation; 7.1 Introduction; 7.2 Making Use of Weaker Feedback; 7.3 Correcting Errors with Speech Recognition; 7.4 Correcting Errors with Handwritten Text Recognition; 7.5 Tasks, Experiments and Results; 7.6 Conclusions; References; Chapter 8: Incremental and Adaptive Learning for Interactive Machine Translation; 8.1 Introduction; 8.2 On-Line Learning; 8.3 Related Topics; 8.4 Results
8.5 ConclusionsReferences; Chapter 9: Interactive Parsing; 9.1 Introduction; 9.2 Interactive Parsing Framework; 9.3 Confidence Measures in IP; 9.4 IP in Left-to-Right Depth-First Order; 9.5 IP Experimentation; 9.6 Conclusions; References; Chapter 10: Interactive Text Generation; 10.1 Introduction; 10.2 Interactive Text Generation at the Word Level; 10.3 Predicting at Character Level; 10.4 Conclusions; References; Chapter 11: Interactive Image Retrieval; 11.1 Introduction; 11.2 Relevance Feedback for Image Retrieval; 11.3 Multimodal Relevance Feedback; References
Chapter 12: Prototypes and Demonstrators
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