User customization and user optimization of cochlear implant devices

人工耳蜗植入设备的用户定制和用户优化

基本信息

批准号：
9116401
负责人：
John H.L. Hansen
金额：
$ 19.13万
依托单位：
UNIVERSITY OF TEXAS DALLAS
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-08-01 至 2017-07-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): The current fitting approach adopted for cochlear implant (CI) users falls along the lines of "one-size-fits-all", in that it is assumed that the initial fitting in the clinic should work equally well in all listening environments. Speech coding algorithms and associated parameters (e.g., compression function) are fixed and are not optimized in any way by either the patient or clinician for different listening situations (e.g., quiet, music, noise). The present study addresses this major limitation with the use of a portable research speech processor that allows users to: (a) change MAP parameters based on two different outcome measures (subjective quality ratings and consonant intelligibility) (b) customize the MAP to different listening situations for maximum benefit, and (c) collect feedback and allow the recording of real acoustic signals for further analysis. In this study, unilateral, bilateral and bimodal users will participate in double-blind field trials to assess the true benefit of a speech processor that can be easily customized by the users to fit their needs based on subjective quality ratings or speech intelligibility measures. The overarching hypothesis of this project is that maximum benefit, both in terms of subjective quality and intelligibility, can be obtained when the cochlear implant devices are customized (by the users) to the various listening situations. The outcomes of the field studies will tell us about the difficulties experienced by CI users in real-world situations as well as the value and additional benefit of customizing speech coding algorithms to different environments, all based on feedback from CI users. Such feedback and user interaction can not be gathered using existing commercial processors, yet it is critically needed to move the field forward.

描述（由申请人提供）：针对人工耳蜗（CI）用户采用的当前拟合方法属于“单身适合所有”的线，因为假定诊所中的初始配件在所有听力环境中都应同样良好。语音编码算法和相关参数（例如，压缩函数）是固定的，并且在不同的听力情况下（例如，安静，音乐，噪音），患者或临床医生都不会以任何方式优化。本研究通过使用便携式研究语音处理器来解决这一主要限制，该处理器允许用户：（a）基于两种不同的结果指标（主观质量评级和辅音清晰度）更改地图参数（b）将地图自定义为不同的听力情况，以及（c）收集反馈并允许记录实际声学信号以进一步分析。在这项研究中，单方面，双边和双峰用户将参加双盲野外试验，以评估用户可以轻松自定义语音处理器的真正好处，以根据主观质量评级或语音清晰度措施来适应其需求。该项目的总体假设是，在主观质量和清晰度方面，当人工耳蜗植入设备（由用户）针对各种听力情况定制时，最大的好处都可以获得。现场研究的结果将告诉我们CI用户在现实情况下遇到的困难，以及将语音编码算法自定义到不同环境的价值和额外好处，这都是基于CI用户的反馈。这种反馈和用户互动无法使用现有的商业处理器收集，但是要向前推进该领域是至关重要的。

项目成果

期刊论文数量（34）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A Dual-Microphone Speech Enhancement Algorithm Based on the Coherence Function.

DOI：
10.1109/tasl.2011.2162406
发表时间：
2011-07-18
期刊：
IEEE transactions on audio, speech, and language processing
影响因子：
0
作者：
Yousefian N;Loizou PC
通讯作者：
Loizou PC

SNR Loss: A new objective measure for predicting speech intelligibility of noise-suppressed speech.

DOI：
10.1016/j.specom.2010.10.005
发表时间：
2011-03-01
期刊：
SPEECH COMMUNICATION
影响因子：
3.2
作者：
Ma, Jianfen;Loizou, Philipos C.
通讯作者：
Loizou, Philipos C.

A NEW MASK-BASED OBJECTIVE MEASURE FOR PREDICTING THE INTELLIGIBILITY OF BINARY MASKED SPEECH.

一种基于掩码的新客观测量方法，用于预测二进制掩码语音的清晰度。

DOI：
10.1109/icassp.2013.6639025
发表时间：
2013
期刊：
Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference)
影响因子：
0
作者：
Yu,Chengzhu;Wójcicki,KamilK;Loizou,PC;Hansen,JohnHL
通讯作者：
Hansen,JohnHL

Estimators of The Magnitude-Squared Spectrum and Methods for Incorporating SNR Uncertainty.