首页|智能辅听系统对改善人工耳蜗植入者听声效果的研究

智能辅听系统对改善人工耳蜗植入者听声效果的研究

The Effects of the Intelligent Hearing-assistive System on Hearing Benefits to Cochlear Implant Recipients

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目的 了解诺尔康人工耳蜗处理器中搭载的智能辅听系统自动识别声音场景并进行智能化的声音处理策略配置及其在改善人工耳蜗植入者主客观听声效果方面的作用.方法 为评估诺尔康智能辅听系统中声音场景识别模块的性能:①为评估场景识别模块的性能,在隔声室环境中播放预设的语音、噪声、带噪语音、纯音乐主带人声音乐5种测试音频(每类测试音频包括6~9个5 min时长的测试文件),统计各类音频的识别准确率和场景切换次数;②为评估该系统中语音增强模块中的ABeam技术的降噪效果,招募13例诺尔康人工耳蜗植入者,分别在ABeam"ON"和"OFF"程序下,在90°、180°、270°三种噪声源角度,测试其言语识别率,并对其主观听声感受进行VAS评估.结果 场景识别模块对各类声音场景的识别准确率分别为语音99%±4%,噪声96%±9%,带噪语音94%±12%,纯音乐94%±15%,带入声音乐92%±13%,预测准确度高;5 min内的场景切换次数分别为语音1.1±0.3次,噪声1.4±0.7次,带噪语音1.3±0.5次,纯音乐1.4±0.8次,带人声音乐1.3±0.5次,预测稳定性较高.当噪声来自侧后方而语音来自正前方时,自适应双麦降噪算法ABeam能够在信噪比为5 dB的噪声环境下显著提高受试者的言语识别率(P<0.001),平均言语识别率提升15.92%.尤其是当噪声来自于正后方180°,开启ABeam能够让受试者的言语识别率显著提高28.68%(P<0.01).结论 智能辅听系统能够帮助人工耳蜗植入者在不同环境下自动选择合适的声音处理策略,提升其言语可懂度和听声效果.
Objective To study the effects of the intelligent hearing-assistive system incorporated in Nuro-tron cochlear implants(CI),including the autonomic acoustic scene recognition(ASR),intelligent strategy config-uration as well as the objective and subjective hearing improvements on recipients.Methods ① To evaluate the per-formance of the ASR matule,in a sound-proof room,the preset five kinds of test audios,including speech,noise,speech in noise,pure music(without human voice)and non-pure Music(with human voice)were played.Each type of scenes included 6 to 9 5 min test files.The prediction accuracy and scene switching times were calculated.② In order to evaluate the noise-reduction performance of the ABeam technology in the speech enhancement module,13 Nurotron® CI recipients were recruited and their speech recognition rate when ABeam was"ON"and"OFF"with noise coming from 90°,180°or 270°were tested,individually.Also,their subjective hearing feedback was evaluated through visual analogue scale(VAS)evaluation.Results The ASR module achieved high prediction performance,with prediction accuracy 99%±4%,96%±9%,94%±12%,94%±15%,92%±13%for speech,noise,noisy speech,pure music and non-pure music,respectively.The scene transation times for each individual scene were 1.1 ±0.3,1.4±0.7,1.3±0.5,1.4±0.8 and 1.3±0.5,indicating that the prediction was also stable.When noise came from the sides and behind of recipients and speech signal from the front,the adaptive dual microphone noise re-duction algorithm ABeam significantly increased the speech recognition score(SRS)in 5 dB signal-to-noise(SNR)environment(P<0.001),with an average increase of 15.92%.Especially when the noise came from 180 degree backward,the SRS increased 28.68%when ABeam was"0N",which was significantly higher than when ABeam was"OFF"(P<0.01).Conclusion The intelligent hearing-assistive system can help CI recipients automatically configure appropriate SPSs under different environments,improving the speech intelligibility and hearing comfort.

Cochlear implantIntelligent hearing-assistive systemAcoustic scene recognitionSound processing strategiesABeam

项丽阳、李娟娟、韩彦、王金剑、杨典、杨婷君、银力、黄穗

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浙江诺尔康神经电子科技股份有限公司(杭州 310011)

浙江省神经电子与脑机接口技术重点实验室

深圳市龙岗区耳鼻咽喉医院

人工耳蜗 智能辅听系统 声音场景识别 声音处理策略 ABeam

浙江省重点研发计划浙江省重点企业研究院项目

2020C03068

2024

听力学及言语疾病杂志
武汉大学人民医院

听力学及言语疾病杂志

CSTPCD北大核心
影响因子:1.16
ISSN:1006-7299
年,卷(期):2024.32(1)
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