CHS: Small: Game for Cleft Speech Therapy
CHS:小型:唇裂言语治疗游戏
基本信息
- 批准号:1617253
- 负责人:
- 金额:$ 50万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-07-15 至 2021-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Orofacial clefts (i.e., cleft lip, cleft lip and palate, and isolated cleft palate, as well as the rare median, lateral [transversal], and oblique facial clefts) are among the most common congenital anomalies. Approximately 20 infants are born in the United States with orofacial clefts on an average day, or 7500 every year. With a cleft palate, one is unable to stop airflow through the nose using normal mechanisms; cleft palate speech therefore contains sounds with air leaking out of the nose, referred to as "nasal escape." In the world of trial-and-error that governs speech learning, the child uses the only tool s/he has available to keep air from escaping out of the nose; s/he holds it back at the level of the glottis or larynx. This mechanism is used by the normal voice to make a hard 'g' as in 'go.' The child uses this "glottal stop" as a substitute for a variety of sounds that s/he cannot create normally. Cleft palate speech thus becomes a collection of sounds characterized by glottal stops and inappropriate nasal escape; these anomalous articulation patterns are usually referred to as compensatory articulation disorder (CAD), and they severely affect speech intelligibility. For this reason, corrective surgery is commonly performed around 10-12 months of age, with the goal of providing a more normal anatomical framework by the time the child begins practicing speech. The repaired palate continues, however, to be variably impaired by the less-than-normal muscle bulk typical of cleft palates and by the stiffness of normal post-surgical scar tissue. Over perhaps one year following surgical repair, palatal function spontaneously improves to the point where in the majority of children it is adequate to selectively prevent nasal escape. Speech therapy after surgery to correct CAD begins at the age of two years and often continues for many years. Correcting cleft speech is important for the child's future ability to live independently and to participate fully in society. Despite the documented benefits, it is a challenge for speech pathologists to train children in proper speech production at an early age when the likelihood of success is highest, because young children are typically less cooperative, sometimes do not fully comprehend what they are being asked to do, and are often unwilling to do unrewarding speech homework, typically under the guidance of inexperienced parents who are unable to assess subtle progress (or lack thereof). The PI's goal in this research is to understand the best strategy for helping children with corrected cleft palate produce normalized speech, and to facilitate this process through games that children can use at home with minimal help from parents while allowing data relating to the child's progress to be delivered to speech pathologists in real time. Project outcomes will especially benefit children from underserved populations. A cleft speech corpus will benefit researchers working on speech recognition algorithms for cleft speech detection, and new speech engine algorithms will benefit speech therapy at large. The work will also spur development of a new research focus at UCSC and UCD in human-centered games for health and healthy living.A major scientific contribution of this project will be a deeper understanding of the determining characteristics of children with cleft palate and how these relate to the phonetic and phonological rule causes of cleft speech. The technological contributions will be the games and speech engines that are procedurally generated to support in-home and independently administered speech therapy for children with corrected cleft palate, and an algorithm that enables longitudinal voice data curation and analysis to be carried out in real time over the intervention history for every participant as well as across participants. Methodological contribution will include a measure of error rates when a speech recognition system is designed to pick up cleft-specific mispronunciations, and a method for conducting participatory design of games for speech therapy involving computer scientists, engineers, developmental psychologists, speech and language pathologists, plastic surgeons, and children with corrected cleft palate and their parents.
口面裂(即,唇裂、唇腭裂、孤立性腭裂,以及罕见的正中、侧面[横向]和斜面裂)是最常见的先天性异常。 在美国,平均每天大约有20名婴儿出生时患有口面裂,或者每年有7500名婴儿出生。 腭裂患者无法用正常的机制阻止气流通过鼻子,因此腭裂语音中含有空气从鼻子泄漏出来的声音,称为“鼻逸”。“在控制语言学习的试错法世界中,孩子使用他/她唯一可用的工具来防止空气从鼻子中逸出;他/她将空气保持在声门或喉部的水平。 这个机制是由正常的声音,使一个硬的“g "在”去“。“孩子用这种‘声门塞音’来代替他/她不能正常发出的各种声音。 因此,腭裂语音成为一个集合的声音,其特征是声门塞音和不适当的鼻逸音;这些异常的发音模式通常被称为代偿性发音障碍(CAD),它们严重影响语音清晰度。 由于这个原因,矫正手术通常在10-12个月大的时候进行,目的是在孩子开始练习说话的时候提供一个更正常的解剖框架。 然而,修复后的腭继续受到腭裂典型的肌肉体积小于正常和正常手术后疤痕组织僵硬的影响。 在手术修复后的一年内,腭功能自发地改善到大多数儿童足以选择性地防止鼻漏的程度。 矫正CAD的手术后语言治疗从两岁开始,通常持续多年。 矫正唇裂言语对孩子未来独立生活和充分参与社会的能力至关重要。 尽管有文件证明的好处,但对于语言病理学家来说,在成功的可能性最高的早期训练儿童正确的语言产生是一个挑战,因为年幼的儿童通常不太合作,有时不能完全理解他们被要求做什么,并且通常不愿意做没有回报的演讲作业,通常是在缺乏经验的父母的指导下,他们无法评估微妙的进展(或缺乏进展)。 PI在这项研究中的目标是了解帮助腭裂矫正儿童产生正常语音的最佳策略,并通过游戏促进这一过程,儿童可以在家里使用,父母的帮助最小,同时允许将与儿童进展有关的数据真实的时间提供给语音病理学家。 项目成果将特别有利于得不到充分服务人口的儿童。 唇裂语音语料库将有利于研究唇裂语音检测的语音识别算法的研究人员,新的语音引擎算法将有利于语音治疗。 这项工作也将刺激在UCSC和UCD在以人为本的游戏健康和健康living.A主要科学贡献的新的研究重点的发展将是更深入地了解腭裂儿童的决定性特征,以及这些如何与语音和语音规则的原因腭裂语音。 技术贡献将是程序生成的游戏和语音引擎,以支持对腭裂矫正儿童的家庭和独立管理的语音治疗,以及一种算法,该算法能够在每个参与者以及参与者的干预历史中以真实的时间进行纵向语音数据管理和分析。 方法学的贡献将包括一个错误率的措施时,语音识别系统的设计,以拿起裂缝特定的发音错误,并进行参与式设计的游戏,涉及计算机科学家,工程师,发展心理学家,语音和语言病理学家,整形外科医生,矫正腭裂儿童和他们的父母的语音治疗的方法。
项目成果
期刊论文数量(0)
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Sri Kurniawan其他文献
Review of Interaction design
- DOI:
10.1145/967199.967218 - 发表时间:
2003-03 - 期刊:
- 影响因子:0
- 作者:
Sri Kurniawan - 通讯作者:
Sri Kurniawan
Vocal interaction: beyond traditional automatic speech recognition
- DOI:
10.1007/s10209-008-0134-z - 发表时间:
2008-08-07 - 期刊:
- 影响因子:2.700
- 作者:
Sri Kurniawan;Adam J. Sporka;Susumu Harada - 通讯作者:
Susumu Harada
ChatGPT, Google Assistant: Which is best for patients with amblyopia? (Preprint)
ChatGPT、Google Assistant:哪个最适合弱视患者?
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:7.4
- 作者:
Gloria Wu;David Lee;Weichen Zhao;Adrial Wong;Rohan Jhangiani;Sri Kurniawan - 通讯作者:
Sri Kurniawan
Towards a Human-centered Tutorial Design for the Nautilus Cluster
迈向以人为本的 Nautilus 集群教程设计
- DOI:
10.1145/3569951.3597601 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Jeffrey Weekley;Sri Kurniawan - 通讯作者:
Sri Kurniawan
Google Assistant and ChatGPT: Is it Useful for Non Medical Professionals Looking for Information about Stroke or Glaucoma?
Google Assistant 和 ChatGPT:对于寻找中风或青光眼信息的非医疗专业人士有用吗?
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Gloria Wu;Shweta Satheesha Krishna;Samantha Sakai;Rohan Jhangiani;Sri Kurniawan - 通讯作者:
Sri Kurniawan
Sri Kurniawan的其他文献
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{{ truncateString('Sri Kurniawan', 18)}}的其他基金
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SCH: INT: Collaborative Research: Replicating Clinic Physical Therapy at Home: Touch, Depth, and Epidermal Electronics in an Interactive Avatar System
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