Audio Processing for Cochlear Implants

人工耳蜗的音频处理

• 批准号: 7850344
• 负责人: Qian-Jie Fu
• 金额: $ 19.16万
• 依托单位: HOUSE RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-17 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7850344
• 关键词: Acoustics; Algorithms; Attenuated; Auditory; Characteristics; Clinical; Cochlear Implants; Doctor of Philosophy; Environment; Exposure to; Financial compensation; Frequencies; Goals; Implanted Electrodes; Individual; Long-Term Effects; Maps; Measures; Modification; Music; Noise; Outcome; Patients; Pattern; Pattern Recognition; Performance; Phase; Pitch Perception; Play; Process; Property; Psychophysiology; Research; Research Personnel; Resolution; Role; Scheme; Signal Transduction; Speech; Techniques; base; computerized data processing; experience; improved; interest; novel; programs; relating to nervous system; research study; response; speech processing; speech recognition; transmission process

DESCRIPTION (provided by applicant): The long-term goal of this research is to improve cochlear implant patient performance by maximizing both the transmission and reception of acoustic patterns. We hypothesize that, due to the loss of fine spectral details, cochlear implant patients have great difficulty in challenging listening conditions (e.g., noise, competing speech, reverberation, unfamiliar talkers, etc.). We propose to optimize the input acoustic signal in response to the acoustic environment, or to different speaker characteristics, thereby improving the transmission of speech patterns. We further hypothesize that poor patient performance may be partly due to sub-optimal settings of important speech processor parameters (e.g., stimulation mode, frequency allocation, stimulation rate, etc.). We propose to optimize these parameters according to individual patients' psychophysical capabilities, thereby improving the reception of speech patterns. Combining these two approaches - pre-processing the input signal and optimizing processor parameters - will provide the greatest benefit to patient performance for a variety of listening conditions. There are three specific aims in the proposed research. Specific aim 1 is to improve the transmission of acoustic patterns. We will evaluate novel speech enhancement algorithms that optimize the input acustic patterns in response to the acoustic environment, or to different speaker characteristics. Specific aim 2 is to improve the reception of acoustic patterns. We will explore the perceptual space for important speech processor parameters and optimize these parameters according to individual patients' psychophysical capabilities. Specific aim 3 is to evaluate the long-term effects of changes to speech processing. While we will generally study the effects of each optimization technique independently in each experiment, the techniques can be easily combined to further optimize audio processing for cochlear implants, once the parameter space is defined. Each of the proposed strategies seeks to optimize some aspect of speech processing and, when combined, the benefit from one strategy may be directly enhanced by the benefit from another. This synergy may further improve patient performance for a wide variety of listening conditions. The proposed research is of great clinical importance in terms of maximizing patient performance under a variety of listening conditions. It is also of great theoretical interest in terms of understanding the neural and perceptual mechanisms involved in pattern recognition.

描述（由申请人提供）：本研究的长期目标是通过最大限度地提高声学模式的传输和接收来改善人工耳蜗植入患者的性能。我们假设，由于失去了精细的频谱细节，人工耳蜗植入患者在挑战听力条件（例如，噪声、竞争语音、混响、不熟悉的谈话者等）。我们建议响应于声学环境或不同的扬声器特性来优化输入声学信号，从而改善语音模式的传输。我们进一步假设，患者表现不佳可能部分是由于重要语音处理器参数的次优设置（例如，刺激模式、频率分配、刺激速率等）。我们建议根据个别患者的心理物理能力来优化这些参数，从而改善语音模式的接收。结合这两种方法-预处理输入信号和优化处理器参数-将为各种听力条件下的患者性能提供最大的好处。在拟议的研究中有三个具体目标。具体目标1是改善声学模式的传输。我们将评估新的语音增强算法，优化输入的声学模式，以响应声学环境，或不同的扬声器特性。具体目标2是改善声学模式的接收。我们将探索重要的语音处理器参数的感知空间，并根据个体患者的心理物理能力优化这些参数。具体目标3是评估语音处理变化的长期影响。虽然我们通常会在每个实验中独立研究每种优化技术的效果，但一旦定义了参数空间，这些技术就可以很容易地组合起来，以进一步优化人工耳蜗的音频处理。所提出的策略中的每一个都试图优化语音处理的某些方面，并且当组合时，来自一个策略的益处可以通过来自另一个策略的益处而直接增强。这种协同作用可以进一步改善患者在各种收听条件下的表现。拟议的研究是非常重要的临床意义，最大限度地提高患者的性能在各种听力条件下。在理解模式识别中涉及的神经和感知机制方面，它也具有很大的理论意义。