KSPC (Keystrokes per Character) as a Characteristic of Text Entry Techniques
Mobile HCI '02 Proceedings of the 4th International Symposium on Mobile Human-Computer Interaction
Characterizing and recognizing spoken corrections in human-computer dialogue
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
A spelling correction program based on a noisy channel model
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 2
Pronunciation modeling for improved spelling correction
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Identifying user corrections automatically in spoken dialogue systems
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
An improved error model for noisy channel spelling correction
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Characterizing and Predicting Corrections in Spoken Dialogue Systems
Computational Linguistics
A phrase-based statistical model for SMS text normalization
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Text Entry Systems: Mobility, Accessibility, Universality
Text Entry Systems: Mobility, Accessibility, Universality
Investigation and modeling of the structure of texting language
International Journal on Document Analysis and Recognition
Extending autocompletion to tolerate errors
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Normalizing SMS: are two metaphors better than one?
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Using the web for language independent spellchecking and autocorrection
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
A practical examination of multimodal feedback and guidance signals for mobile touchscreen keyboards
Proceedings of the 12th international conference on Human computer interaction with mobile devices and services
ASWC'06 Proceedings of the First Asian conference on The Semantic Web
Towards online adaptation and personalization of key-target resizing for mobile devices
Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
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Text input aids such as automatic correction systems play an increasingly important role in facilitating fast text entry and efficient communication between text message users. Although these tools are beneficial when they work correctly, they can cause significant communication problems when they fail. To improve its autocorrection performance, it is important for the system to have the capability to assess its own performance and learn from its mistakes. To address this, this paper presents a novel task of self-assessment of autocorrection performance based on interactions between text message users. As part of this investigation, we collected a dataset of autocorrection mistakes from true text message users and experimented with a rich set of features in our self-assessment task. Our experimental results indicate that there are salient cues from the text message discourse that allow systems to assess their own behaviors with high precision.