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Word Segmentation Across Two Languages Via Statistical Learning

Word Segmentation Across Two Languages Via Statistical Learning
通过统计学习进行两种语言的分词
批准号:
RGPIN-2019-06836
负责人:
Fennell, Christopher
金额:
$1.21万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
翻译
统计学习是指跟踪来自周围环境的感官输入的规律模式的能力。考虑到语言的规律性和层次结构,语言本质上是一个基于模式的系统,因此研究人员认为统计学习是语言习得的基础。事实上,幼儿和成人可以通过跟踪音节共现概率并在此基础上提取单词,从而在人工语言中找到单词。然而,之前的研究主要集中在学习者是否能够统计地从单一语言中分词;学习者是否能够从两种人工语言中分词仍然不得而知。鉴于双语的全球普及,双输入分词是必要的。一些研究表明,学习者在强大的说话者特定语境线索(即每种语言与不同的人配对)的支持下,可以成功地分割两种重叠的人工语言。然而,从本质上讲,一个双语个体必须在两种不同的语言之间交替,有时甚至在一次对话中(即代码转换)。因此,探索单个个体言语中的语音上下文线索是否有助于两种人工语言的成人分割是很重要的。因此,我们将研究成人和婴儿学习者,以回答三个问题:(i)学习者能否利用单个人的语音线索成功地从两种人工语言中分词?2)双语者是否优于单语者?3)是否有特定的因素,如认知能力或双语经验,在两种语言的分词中有潜在的双语优势?在我们的第一组研究中,我们检查了成人学习者是否通常可以利用法语和英语的语音线索从两种重叠的人工语言中分词。试点数据表明,基于某些音素的局限性和同时双语的优势。因此,我们建议对同时使用多种语言的人进行测试,使用更明显的音素差异,并在一系列实验中使用非母语语音线索,以充分探索成人在新环境中处理信息的灵活性以及他们对标志着语言输入变化的微妙线索的敏感性。进一步,我们将探讨成人的认知能力是否与学习者的分词表现有关。在第二组研究中,我们将测试9、11和13个月大的婴儿在相同的法语口音和英语口音的人工语言刺激下的双输入分割任务,该任务适用于婴儿。这种发展方法将测试是否在婴儿时期出现双语优势。此外,我们将再次使用执行功能任务测试认知技能,以探索分割和认知能力之间的任何关系。
英文摘要
Statistical learning refers to the ability to track regular patterns in sensory input from ambient environments. Given its regularities and hierarchical structures, language is essentially a pattern-based system and therefore researchers have argued that statistical learning is fundamental to language acquisition. Indeed, young infants and adults can find words in artificial languages by tracking syllable co-occurrence probabilities and extracting words on that basis. However, prior studies have mainly focused on whether learners can statistically segment words from a single language; whether learners can segment words from two artificial languages remains largely unknown. Given the global prevalence of bilingualism, it is necessary to dual-input segmentation. Some studies have demonstrated that learners succeed in segmenting two overlapping artificial languages when supported by strong speaker-specific contextual cues (i.e., each language paired with a different person). However, by nature, a single bilingual individual has to alternate between two distinct languages, sometimes even in one conversation (i.e., code-switching). It is therefore important to explore whether phonetic contextual cues in a single individual's speech can facilitate adult segmentation of two artificial languages. Therefore, we will examine adult and infant learners to answer three questions: (i) Can learners make use of phonetic cues within a single individual's speech to segment words successfully from two artificial languages?; 2) Do bilinguals outperform monolinguals?; and 3) Do specific factors, such as cognitive ability or bilingual experience, underlie any potential bilingual advantage in word segmentation across two languages? In our first group of studies, we examine if adult learners generally could make use of French and English phonetic cues to segment words from two overlapping artificial languages. Pilot data indicated limitations based on certain phonemes and a simultaneous bilingual advantage. We therefore propose to test simultaneous multilinguals, use more salient phoneme differences, and use non-native phonetic cues across a series of experiments to fully explore adults' flexibility in processing information in new environments and their sensitivity to subtle cues that mark the changes of language inputs. Further, we will explore if adults' cognitive abilities are related to learners' segmentation performance. In the second set of studies, we will test infants of 9, 11, and 13 months on the same French-accented versus English-accented artificial language stimuli in a dual input segmentation task adapted for infants. This developmental approach will test if any bilingual advantages emerge in infancy. Further, we will again test cognitive skills using a executive functioning task to explore any relationship between segmentation and cognitive ability.
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Word Segmentation Across Two Languages Via Statistical Learning
  • 批准号:
    RGPIN-2019-06836
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.21万
  • 财政年份:
    2021
  • 负责人:
    Fennell, Christopher
  • 依托单位:
Word Segmentation Across Two Languages Via Statistical Learning
  • 批准号:
    RGPIN-2019-06836
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.21万
  • 财政年份:
    2020
  • 负责人:
    Fennell, Christopher
  • 依托单位:
Word Segmentation Across Two Languages Via Statistical Learning
  • 批准号:
    RGPIN-2019-06836
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.21万
  • 财政年份:
    2019
  • 负责人:
    Fennell, Christopher
  • 依托单位:
Attentional processes in infant bilinguals
  • 批准号:
    RGPIN-2014-04590
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2018
  • 负责人:
    Fennell, Christopher
  • 依托单位:
海外基金