The Effects of Quantized Re-timing of Speech Rhythm on Spoken Language

语音节奏量化重定时对口语的影响

• 批准号: 2194772
• 金额: --
• 依托单位: University of Glasgow
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2194772
• 关键词: Effects; Quantized; Re; timing; Speech

OverviewWhat's going to happen next? is a question the brain constantly seeks to answer. Inneuroscience, prediction is increasingly seen as the key to language comprehension, but lessis known about how listeners predict when linguistic events (sounds, syllables) will occur,than about what is coming. Current theories of neural speech processing suggest a key rolefor rhythm, yet neuroscience and the speech sciences lack a shared understanding of thebasics of rhythm. This project seeks to address this gap by asking: Can speech be re-timed soas to maximise its comprehensibility? The research will use phonetic and musicalapproaches to inform the re-timing of speech and the effects on comprehension will betested using innovative eye-tracking and EEG paradigms.ContextA crucial aspect of speech comprehension is the ability to anticipate lexical or grammaticalunits. This has been demonstrated by extensive research showing characteristic neuralresponses to violations of expectation in speech (e.g. Hagoort et al., 2004). According torecent theories in cognitive neuroscience, listeners achieve such anticipation in part bytracking regularities in speech rhythm, at timescales roughly corresponding to individualvowels and consonants, and to syllables (e.g. Giraud and Poeppel, 2012; Gross et al., 2013).However, this picture does not match well with phonetic or behavioural reality. First, thereis little evidence of rhythmic regularity in the production of syllables in naturally occurringspeech (Cummins, 2012). Second, the rhythm-tracking approach suggests that makingspeech more regular would help comprehension. But, while presenting isolated syllables atregular time intervals can yield processing benefits (Otterbein et al., 2012), regularising theintervals between syllables in connected speech instead has a processing cost (Aubanel etal., 2016). In sum, regularity can be beneficial, but is not always: the relationships have to beright for the speech being presented, in ways that are poorly understood.A speech signal does not necessarily need to be regular to be rhythmic. In response tomusical rhythms, neural correlates of the pulse (or beat) can be found when listeners arepresented with complex polyrhythms where the pulse is not physically present in the signal(Tal et al., 2017). Similar principles might apply in speech, but the relevant empirical workhas not been done, and speech research has a much reduced lexicon of terminology forrhythm compared to music (Smith et al, 2014). In order to understand how the temporalcharacteristics of speech facilitate comprehension, it may be necessary to consider a morenuanced approach to rhythm, informed by music.This project seeks to improve understanding of the role of rhythm in speech comprehensionby answering two Research questions:1. Does re-timing speech to increase its rhythmicity help speech comprehension, when amore sophisticated approach than equalising syllable durations is used?2. If so, on which properties of the speech signal should re-timing ideally be based?

概述接下来会发生什么？是大脑不断寻求答案的问题在神经科学中，预测越来越多地被视为语言理解的关键，但很少有人知道听众如何预测语言事件（声音，音节）何时发生，而不是什么。目前的神经语音处理理论认为节奏是一个关键的角色，然而神经科学和语音科学缺乏对节奏基础的共同理解。这个项目旨在解决这个问题的差距：讲话可以重新计时，以便最大限度地提高其可理解性？这项研究将使用语音和音乐的方法来通知重新定时的讲话和理解的影响将被测试使用创新的眼动跟踪和EEG paradigm.ContextA语音理解的一个重要方面是预测词汇或语法单位的能力。这已经被广泛的研究所证明，这些研究显示了对言语中违反期望的特征性神经反应（例如，Hagoort等人，2004年）。根据认知神经科学的最新理论，听众通过跟踪语音节奏的变化来实现这种预期，其时间尺度大致对应于单个元音和辅音以及音节（例如Giraud和Poeppel，2012; Gross等人，然而，这一情况与语音或行为现实并不相符。首先，在自然发生的语音中，几乎没有证据表明音节产生的节奏规律性（康明斯，2012）。第二，节奏追踪法表明，使讲话更有规律有助于理解。但是，虽然以规则的时间间隔呈现孤立的音节可以产生处理益处（Otterbein等人，2012），而在连接的语音中调整音节之间的间隔则会产生处理成本（Aubanel埃塔尔，2016年）。总而言之，规律性可能是有益的，但并不总是如此：这些关系必须以人们难以理解的方式适合于所呈现的语音。语音信号不一定需要规则才能有节奏。响应于音乐节奏，当听众呈现复杂的多节律时，可以发现脉冲（或节拍）的神经相关性，其中脉冲在信号中不物理存在（Tal等人，2017年）。类似的原则可能适用于语音，但相关的实证工作尚未完成，与音乐相比，语音研究的节奏术语词汇量要少得多（Smith et al，2014）。为了理解语音的时间特征如何促进理解，可能有必要考虑一种更先进的方法来理解节奏，通过音乐来理解。当使用比均衡音节持续时间更复杂的方法时，重新计时语音以增加其节奏性是否有助于语音理解？2.如果是这样，理想的重定时应该基于语音信号的哪些属性？