CAREER: Finite-State Machine Learning on Strings and Sequences

这个CAREER项目旨在为序列数据的统计建模创建一个软件基础结构。用户将能够指定、训练、应用、组合和共享模型。例如，要建立一个从文本中提取信息或将文本翻译成另一种语言的系统，可以将其他几个研究人员的各种语言现象模型结合起来。所得到的复合模型在其结构中反映了专家知识，但它也有可以在适当的数据上训练的自由参数。技术方法是用加权多带有限状态自动机来表示统计模型。序列数据、序列处理工具和关系数据库也可以用这种格式表示。所有这些资源都可以使用灵活的正则表达式语言有效地组合起来，因为这类自动机在许多有用的操作下是封闭的。作为构建软件基础设施的一部分，该项目将研究改进的搜索策略和训练算法。在PI的语言和语音处理专业范围内，它还将开发一些有用的模型。该项目旨在让更多的人能够更快地成功地为更多的领域和应用构建更准确、更高效的语音和NLP软件，从而降低现代语言和语音技术的进入门槛。除了通过易于使用的软件和清晰的教程接触社区外，该项目还将开发cs特定的课程材料，逐步深入揭示基本理论和算法。

This CAREER project aims to create a software infrastructure for statistically modeling sequence data. Users will be able to specify, train, apply, combine, and share models. For instance, to build a system for extracting information from text, or translating text into another language, one might combine several other researchers' models of various linguistic phenomena. The resulting composite model reflects expert knowledge in its structure, but it also has free parameters that can be trained on appropriate data.The technical approach is to represent statistical models with weighted multi-tape finite-state automata. Sequence data, sequence processing tools, and relational databases can also be represented in this format. All these resources can be efficiently combined, using a flexible regular-expression language, because this class of automata is closed under many useful operations. As part of building the software infrastructure, the project will investigate improved search strategies and training algorithms. Within the PI's specialty of language and speech processing, it will also develop some useful models.This project is designed to allow more people to succeed more quickly at building more accurate and efficient speech and NLP software for more domains and applications, thus lowering the barriers to entry in modern language and speech technology. Besides reaching out to communities through easy-to-use software and clear tutorials, the project will develop CS-specific course materials that gradually dig down to reveal the fundamental theory and algorithms.