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SimPhon.Net - Usage-based approaches, computational modeling and simulation studies in phonetics and phonology

SimPhon.Net - 语音学和音系学中基于使用的方法、计算建模和模拟研究

基本信息

批准号：
282025732
负责人：
Dr. Daniel Duran
金额：
--
依托单位：
Forschungsbereich Laborphonologie
依托单位国家：
德国
项目类别：
Scientific Networks
财政年份：
2015
资助国家：
德国
起止时间：
2014-12-31 至 2020-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/282025732?language=en
关键词：
SimPhon.Net Usage based approaches computational

项目摘要

Two kinds of research methodology are often discussed in phonetic sciences: field work, observing its subject ofstudy in situ, and experimental or laboratory work, studying speech in vitro. Both observe language in vivo onliving, speaking humans. This network is concerned with a third kind of research method that recently emerged:the study of language and speech by means of computational modeling and simulations, observing the subjectof study in silico. Fant [2004] noticed a transition from analogue to digital processing in speech research. Thistrend towards digitization is still in progress, manifesting itself in the emergence of simulation-based methodology.However, simulations are not considered common practice, yet. They require familiarity with artificial intelligenceand machine learning. Thus, such experiments can be performed only by a phonetician or phonologist with astrong background in computational linguistics, or in close interdisciplinary collaboration between linguists andcomputer scientists. SimPhon.Net will address that challenge, each member contributing their expertise and experience. Combining this knowledge within the network, we will review and advance on the state of the art, and identify most promising approaches and most important challenges.

语音学中经常讨论两种研究方法：一种是实地考察，即在现场观察研究对象；另一种是实验或实验室考察，即在体外研究言语。两者都是在活生生的、会说话的人类身上观察语言。本网络关注的是最近出现的第三种研究方法：通过计算机建模和模拟来研究语言和语音，在计算机上观察研究对象。Fant[2004]注意到语音研究中从模拟处理到数字处理的转变。数字化的趋势仍在进行中，体现在基于仿真的方法的出现上。然而，模拟还不被认为是常见的做法。他们需要熟悉人工智能和机器学习。因此，这样的实验只能由具有强大计算语言学背景的语音学家或音韵学家进行，或者在语言学家和计算机科学家之间的密切跨学科合作中进行。SimPhon。Net将应对这一挑战，每个成员都贡献自己的专业知识和经验。结合网络中的这些知识，我们将回顾和推进最先进的技术，并确定最有希望的方法和最重要的挑战。