Automated Test of Word Recognition - Phase II

文字识别自动测试 - 第二阶段

• 批准号: 6936830
• 负责人: ROBERT H MARGOLIS
• 金额: $ 39.76万
• 依托单位: AUDIOLOGY, INC
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2007-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6936830
• 关键词: behavioral /social science research tag; biomedical automation; clinical research; communication disorder diagnosis; computer program /software; diagnosis design /evaluation; diagnosis quality /standard; human subject; method development; multilingualism; nonEnglish language; performance; phonology; psychological tests; speech recognition

DESCRIPTION (provided by applicant): Over 5 million word recognition tests are administered annually by audiologists in the United States with an associated cost of more than $100 million. These tests are currently performed manually by highly trained audiologists. This application describes the Phase II development of automated clinical speech recognition tests using clinical test recordings and an automated speech recognition system to score the subjects' responses. A method for automatically interpreting the test scores will also be evaluated. The objectives are to increase the accuracy and efficiency of these clinical tests, substantially reduce the cost, and provide an objective, automatic, evidence-based method for interpreting the results. The automated speech recognition test in combination with the automated pure tone audiogram (currently an STTR Phase II project) will perform diagnostic testing of a majority of audiology patients, freeing the audiologists' time for activities that require their training and skill. Contemporary changes in training and reimbursement patterns create a high demand for automated clinical procedures. The automated procedures are implemented on existing commercial audiometers with a personal computer that controls the audiometer delivery and routing of stimuli. Phase I results were obtained with automatic speech recognizers that were trained on a limited number of subjects (n=9). Estimates of the agreement between human and machine scoring ranged from 82-93%. Additional refinements with benefits that are predictable from prior experience will increase recognizer performance to a level that equals or exceeds human-human agreement and provide the basis for efficient and accurate clinical tests. In Phase II, an automatic speech recognition threshold test will be compared to the manual method used in routine clinical practice. Two different recognizer scoring strategies will be developed, one that requires more test time but is independent of individual speaker differences and is easily adaptable to other languages, and one that requires less time but may not be applicable to all patients. A pilot study will test the method on a Spanish-language speech-recognition test.

描述（由申请人提供）：美国听力学家每年管理超过500万个单词识别测试，相关成本超过1亿美元。这些测试目前由训练有素的听力学家手动执行。该应用程序描述了使用临床测试记录和自动语音识别系统对自动临床语音识别测试的II期开发，以评分受试者的反应。还将评估一种自动解释测试分数的方法。这些目的是提高这些临床测试的准确性和效率，从而大大降低成本，并提供一种基于客观的，基于证据的方法来解释结果。自动语音识别测试与自动化的纯音听力图（目前是STTR II期项目）将对大多数听力学患者进行诊断测试，从而腾出了听力学家进行需要培训和技能的活动的时间。当代培训和报销模式的变化对自动临床程序产生了很高的需求。自动化过程是在现有的商业听力计上实现的，该个人计算机可以控制刺激的听力计的传递和路由。通过对有限数量的受试者进行培训的自动语音识别器获得了I期结果（n = 9）。人类和机器评分之间一致性的估计范围为82-93％。从先前的经验中可以预测的带有可预测的收益的其他细化将使识别效果提高到等于或超过人类一致的水平，并为有效，准确的临床测试提供了基础。在第二阶段，将将自动语音识别阈值测试与常规临床实践中使用的手动方法进行比较。将制定两种不同的识别器评分策略，一种需要更多的测试时间，但独立于单个说话者的差异，并且很容易适应其他语言，一种需要更少的时间，但可能不适用于所有患者。一项试点研究将测试西班牙语语音识别测试的方法。