This paper introduces to the finite-state calculus a family of directed replace operators. In contrast to the simple replace expression, UPPER -> LOWER, defined in Karttunen (1995), the new directed version, UPPER @-> LOWER, yields an unambiguous transducer if the lower language consists of a single string. It transduces the input string from left to right, making only the longest possible replacement at each point. A new type of replacement expression, UPPER @-> PREFIX … SUFFIX, yields a transducer that inserts text around strings that are instances of UPPER. The symbol … denotes the matching part of the input which itself remains unchanged. PREFIX and SUFFIX are regular expressions describing the insertions. Expressions of the type UPPER @-> PREFIX … SUFFIX may be used to compose a deterministic parser for a ‘local grammar’ in the sense of Gross (1989). Other useful applications of directed replacement include tokenization and filtering of text streams.
Directed Replacement
| Lauri Karttunen |
| Proceedings of ACL'96. Santa Cruz, CA, June 23-28 1996. pp.108-115 |
The research we conduct on expressive visual representations is applicable to visual search, object detection, image classification and the automatic extraction of 3D human poses and shapes that can be used for human behavior understanding and prediction, human-robot interaction or even avatar animation. We also extract 3D information from images that can be used for intelligent robot navigation, augmented reality and the 3D reconstruction of objects, buildings or even entire cities.
Our work covers the spectrum from unsupervised to supervised approaches, and from very deep architectures to very compact ones. We’re excited about the promise of big data to bring big performance gains to our algorithms but also passionate about the challenge of working in data-scarce and low-power scenarios.
Furthermore, we believe that a modern computer vision system needs to be able to continuously adapt itself to its environment and to improve itself via lifelong learning. Our driving goal is to use our research to deliver embodied intelligence to our users in robotics, autonomous driving, via phone cameras and any other visual means to reach people wherever they may be.
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