音标系统的跨语言数据库

Cormac Anderson, Tiago Tresoldi, T. Chacon, Anne-Maria Fehn, M. Walworth, Robert Forkel, Johann-Mattis List
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引用次数: 43

摘要

与非从业者可能期望的相反,语言学家使用的音标系统是非常特殊的。不仅不同的语言学子领域在它们用来表示语言语音的具体符号上存在分歧,而且在声音清单的大型数据库中也可以发现相当大的差异。受最近在不同资源的参考目录(Glottolog, Concepticon)的帮助下连接跨语言数据的努力的启发,我们提出了将不同的语音符号系统连接到语音目录的初步努力。这是在数据库的帮助下实现的,软件框架使用有限但易于扩展的非二进制特征值集,允许快速方便地注册不同的转录系统,同时链接到具有有限库存的其他数据集。连接不同的转录系统使我们能够方便地在不同的语音转录系统之间进行翻译,而将声音连接到数据库使用户能够快速访问各种元数据,包括特征值,音素库存统计以及韵律和声音类别信息。为了证明这项事业的可行性,我们补充了我们的跨语言语音转录系统数据库(CLTS)的初始版本,该数据库目前注册了五个转录系统并链接到15个数据集,以及一个web应用程序,允许用户方便地测试跨转录系统自动翻译的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A cross-linguistic database of phonetic transcription systems
Abstract Contrary to what non-practitioners might expect, the systems of phonetic notation used by linguists are highly idiosyncratic. Not only do various linguistic subfields disagree on the specific symbols they use to denote the speech sounds of languages, but also in large databases of sound inventories considerable variation can be found. Inspired by recent efforts to link cross-linguistic data with help of reference catalogues (Glottolog, Concepticon) across different resources, we present initial efforts to link different phonetic notation systems to a catalogue of speech sounds. This is achieved with the help of a database accompanied by a software framework that uses a limited but easily extendable set of non-binary feature values to allow for quick and convenient registration of different transcription systems, while at the same time linking to additional datasets with restricted inventories. Linking different transcription systems enables us to conveniently translate between different phonetic transcription systems, while linking sounds to databases allows users quick access to various kinds of metadata, including feature values, statistics on phoneme inventories, and information on prosody and sound classes. In order to prove the feasibility of this enterprise, we supplement an initial version of our cross-linguistic database of phonetic transcription systems (CLTS), which currently registers five transcription systems and links to fifteen datasets, as well as a web application, which permits users to conveniently test the power of the automatic translation across transcription systems.
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