Commercial Readiness of a CI NR algorithm

CI NR 算法的商业准备情况

基本信息

  • 批准号:
    10546391
  • 负责人:
  • 金额:
    $ 102.07万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-04-25 至 2025-05-31
  • 项目状态:
    未结题

项目摘要

PROJECT SUMMARY / ABSTRACT Cochlear implant (CI) users are typically able to maintain conversations in quiet environments. However, when multiple people are talking simultaneously, such as at a large family dinner or in a restaurant, CI users have great difficulty participating in conversations and frequently withdraw or avoid the situation. Ideally, CI algorithms to remove background talkers (“babble”) from the signal will allow for improved comprehension and conversational engagement. Although CIs incorporate noise reduction (NR) algorithms, these algorithms are not effective when the background is babble. Separating babble from a foreground talker poses two significant challenges. First, the spectral properties of the signal and noise are extremely similar as both are speech. Second, the spectral and temporal properties of multi-talker babble change with time and are therefore difficult to predict. Despite these challenges, we developed an extremely effective algorithm called SEDA to remove babble. SEDA improved understanding of speech in babble at all signal-to-noise ratios (SNRs) tested by an average of 26 percentage points (or 38 points, when normalized with respect to hearing in quiet). In contrast, a commercial NR algorithm (ClearVoice from Advanced Bionics) provided little to no detectable benefit. In a successful Phase 2, we produced a commercially viable implementation of SEDA. Nevertheless, significant work is required to bring SEDA to commercial readiness. The Aims below were developed in conjunction with CI manufacturers to facilitate SEDA technology for licensing by CI manufacturers. Aim 1: Evaluate SEDA in non-babble listening situations. At minimum, SEDA must be beneficial with babble and not detrimental in other listening situations if it is to be commercially implemented into a CI. Therefore, we will evaluate the effect of SEDA in non-babble auditory scenes using speech recognition, listener preference, and a computational metric. Aim 2: Interrogate benefits of SEDA relative to commercial offerings from CI manufacturers. We will compare the effectiveness of SEDA with NR from Advanced Bionics, MED-EL, Cochlear, and Oticon Medical on understating speech in babble, white, and speech-shaped noise. Aim 3: Obtain real-world feedback from at home evaluations of SEDA. We will send patients home for a month with SEDA to collect feedback and to ascertain unexpected issues or listening situations to be addressed. Aim 4: Quantify the effects of computational trade-offs on SEDA performance. We will modify the number of parameters used in SEDA to adjust the computational requirements. Using a computational metric and speech recognition, we will evaluate the effects of the of these changes on SEDA’s performance.
项目摘要/摘要

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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David M Landsberger其他文献

David M Landsberger的其他文献

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{{ truncateString('David M Landsberger', 18)}}的其他基金

Stimulating the cochlear apex without longer electrodes
无需较长电极即可刺激耳蜗尖部
  • 批准号:
    10461862
  • 财政年份:
    2021
  • 资助金额:
    $ 102.07万
  • 项目类别:
Stimulating the cochlear apex without longer electrodes
无需较长电极即可刺激耳蜗尖部
  • 批准号:
    10287179
  • 财政年份:
    2021
  • 资助金额:
    $ 102.07万
  • 项目类别:
Removing background talker noise for cochlear implant users
为人工耳蜗用户消除背景说话者噪音
  • 批准号:
    10009945
  • 财政年份:
    2020
  • 资助金额:
    $ 102.07万
  • 项目类别:
Commercial Readiness of a CI NR algorithm
CI NR 算法的商业准备情况
  • 批准号:
    10672315
  • 财政年份:
    2020
  • 资助金额:
    $ 102.07万
  • 项目类别:
Reduction in spread of excitation as predictor multi-channel spectral resolution
减少激励扩散作为预测器多通道光谱分辨率
  • 批准号:
    8727506
  • 财政年份:
    2012
  • 资助金额:
    $ 102.07万
  • 项目类别:
Reduction in spread of excitation as predictor multi-channel spectral resolution
减少激励扩散作为预测器多通道光谱分辨率
  • 批准号:
    8915669
  • 财政年份:
    2012
  • 资助金额:
    $ 102.07万
  • 项目类别:
Reduction in spread of excitation as predictor multi-channel spectral resolution
减少激励扩散作为预测器多通道光谱分辨率
  • 批准号:
    8810293
  • 财政年份:
    2012
  • 资助金额:
    $ 102.07万
  • 项目类别:
Reduction in spread of excitation as predictor multi-channel spectral resolution
减少激励扩散作为预测器多通道光谱分辨率
  • 批准号:
    8373787
  • 财政年份:
    2012
  • 资助金额:
    $ 102.07万
  • 项目类别:
Using current-focusing and current-steering to increase the number of effective c
使用电流聚焦和电流引导来增加有效电流的数量
  • 批准号:
    8247244
  • 财政年份:
    2009
  • 资助金额:
    $ 102.07万
  • 项目类别:
Using current-focusing and current-steering to increase the number of effective c
使用电流聚焦和电流引导来增加有效电流的数量
  • 批准号:
    7851163
  • 财政年份:
    2009
  • 资助金额:
    $ 102.07万
  • 项目类别:

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