Understanding Prosody and Tone Interactions through Documentation of Two Endangered Languages

通过两种濒危语言的记录来理解韵律和声调的相互作用

• 批准号: 1360670
• 负责人: Christian DiCanio
• 金额: $ 34.05万
• 依托单位: Haskins Laboratories, Inc.
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-15 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1360670&HistoricalAwards=false
• 关键词: Understanding; Prosody; Tone; Interactions; through

For accurate automated translation of text-to-spoken-word or spoken-word-to-text, it is necessary to understand the prosodic patterning of speech since prosody, i.e. stress, rhythm, and pauses between phrases, is central in conveying meaning and structuring discourse. In addition, many languages use tone to change the meaning of words but little is known about how prosodic features interact with tone. Since tone and prosody are conveyed by using some of the same acoustic dimensions (pitch, duration, voice quality), one must know how these two systems interact for automatic speech recognition and translation.To investigate and test hypotheses about the relationship of tone and prosody, Christian Di Canio, along with an interdisciplinary team, will create a database of 30 hours of transcribed narratives from Itunyoso Trique and expand an existing similar database in Yoloxóchitl Mixtec, both both Mixtecan languages from eastern central Mexico. These transcribed narratives will then be parsed into smaller units applying a 'forced alignment' tool used in automatic speech recognition. Important results from the project will include the testing and improvement of the forced alignment tool; new corpora and expanded dictionaries for and Yoloxóchitl Mixtec; and an analysis of tone and prosody interactions in these two languages. The resulting prosodically segmented and tagged corpora will be a first of its kind for an endangered language that will be of use to the speaker-community and the broader scientific community.This project is partially supported by funds from the Robust Intelligence program.

为了准确地自动翻译文本到口语单词或口语单词到文本，有必要了解语音的韵律模式，因为韵律，即重音，节奏和短语之间的停顿，是传达意义和构建话语的核心。 此外，许多语言使用音调来改变单词的含义，但对韵律特征如何与音调相互作用知之甚少。 由于音调和韵律是通过使用一些相同的声学维度来传达的（音高、持续时间、语音质量），人们必须知道这两个系统如何相互作用以进行自动语音识别和翻译。为了调查和测试关于音调和韵律关系的假设，克里斯蒂安·迪卡尼奥沿着一个跨学科团队，将创建一个30小时的Itunyoso Trique转录叙述的数据库，并扩展Yoloxóchitl Mixtec现有的类似数据库，这两种语言都来自墨西哥中东部的Mixtecan语言。 然后，这些转录的叙述将被解析成更小的单元，应用自动语音识别中使用的“强制对齐”工具。 该项目的重要成果将包括测试和改进强制对齐工具;新的语料库和扩展的词典和Yoloxóchitl Mixtec;以及对这两种语言中音调和韵律相互作用的分析。 由此产生的韵律分割和标记语料库将是第一个濒危语言，将用于扬声器社区和更广泛的科学界。该项目部分由强大的智能计划的资金支持。