A Common Prosody Platform for Testing Theories and Models of Speech Prosody

用于测试语音韵律理论和模型的通用韵律平台

• 批准号: 1355479
• 负责人: Douglas Whalen
• 金额: $ 28.02万
• 依托单位: Haskins Laboratories, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-03-15 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1355479&HistoricalAwards=false
• 关键词: Common; Prosody; Platform; Testing; Theories

Prosody plays an important role in the complex mapping between meaning and the spoken expression of words, phrases and sentences; it is critical to our understanding of human communication and to our ability to exploit prosodic information in both automated language production and meaning recognition.Prosody research has seen significant development in recent decades, and numerous theories and computational models have been proposed. However, many fundamental issues remain unresolved and some are still under heated debate. This lack of consensus has resulted in slow advances in developing speech applications with capabilities for processing prosody. This project is a collaborative effort to accelerate progress in prosody research by developing a Common Prosody Platform (CPP). CPP will consist of an open-access web site that hosts a collection of trainable models in the form of Praat scripts, each implementing a major theory of prosody. All the scripts will consist of A) a computational realization of the basic assumptions of a particular theory, which is capable of generating surface prosodic forms (initially, F0 and duration), and B) a set of learning algorithms for automatic analysis-by-synthesis and global optimization, which allow the script to be trained on any speech corpora marked up with theory-specific categories. CPP will therefore facilitate theory evaluation by enabling them to make numerical predictions that can be directly compared with natural prosody in fine detail. CPP will be tested on autosegmental-metrical (AM) theory, Parallel Encoding and Target Approximation (PENTA) model, articulatory phonology/task dynamic model (TADA), and command response (Fujisaki) model, and apply them to English, Greek, Mandarin and Itunyoso Trique (an endangered tone language).The development of CPP will help bridge the current gaps between theoretical conceptualization, empirical investigation and computational modeling. The computational nature of the resulting trainable models will also make them readily transferable to applied areas, including speech technology, language teaching and speech communication disorders. The research approach developed in this project may also be extendable to a general paradigm in speech research, namely, theory testing by computational modeling.

韵律在意义与词语、短语和句子的口语表达之间的复杂映射中起着重要作用，它对于我们理解人类交际以及在自动语言生成和意义识别中利用韵律信息的能力至关重要。近几十年来，韵律研究取得了长足的发展，提出了许多理论和计算模型。然而，许多根本性问题仍未解决，一些问题仍在激烈辩论中。这种共识的缺乏导致了开发具有韵律处理能力的语音应用程序的进展缓慢。该项目是一项合作努力，旨在通过开发一个通用韵律平台(CPP)来加速韵律研究的进展。CPP将由一个开放访问的网站组成，该网站以Praat脚本的形式托管一系列可培训的模型，每个模型都实施一种主要的韵律理论。所有的脚本将包括A)特定理论的基本假设的计算实现，其能够生成表面韵律形式(最初，F0和持续时间)，以及B)一组用于自动综合分析和全局优化的学习算法，其允许在标有理论特定类别的任何语音语料库上对脚本进行训练。因此，CPP将通过使他们能够做出可以直接与自然韵律进行详细比较的数值预测来促进理论评估。CPP将在自动分段(AM)理论、并行编码和目标近似(PENTA)模型、发音语音/任务动态模型(TADA)和命令反应(Fujisaki)模型上进行测试，并将它们应用于英语、希腊语、普通话和Itunyoso Trique(一种濒危的声调语言)。CPP的发展将有助于弥合目前理论概念化、经验调查和计算建模之间的差距。由此产生的可训练模型的计算性质也将使它们很容易转移到应用领域，包括语音技术、语言教学和语音沟通障碍。本课题所提出的研究方法也可以扩展到言语研究中的一般范式，即通过计算模型进行理论检验。