优化CI系统以更好地识别软语音——宽范围映射的概念。

IF 1.7 4区医学 Q2 OTORHINOLARYNGOLOGY

Laryngoscope Investigative Otolaryngology Pub Date : 2025-10-07 DOI:10.1002/lio2.70273

Matthias Hey, Thomas Hocke

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引用次数: 0

摘要

目的：人工耳蜗的个性化定位旨在优化使用者的语言理解。最近的研究显示了软语音的重要性：(1)根据Datalog的研究，很大一部分语音成分位于60 dB以下的范围内；(2)软语音在CI结果中代表了一个单独的类别，除了超阈值语音和噪声语音。软语音理解可以受到优化t值或全局参数（Nucleus系统中的响度增长和TSPL）的影响。本研究的重点是通过优化响度增长来改善60分贝以下的软语音。方法：对20例有经验的成年CI使用者在语音处理器CP11 （Cochlear Ltd.）中不同响度增长的语音理解进行比较。引入单音节词在40 dB和50 dB下的平均软语音评分进行量化。结果：研究的20名患者中，有6名在优化响度增长时表现出明显的个体软语改善，而在安静或嘈杂的测试条件下没有人表现出明显的下降。结论：实际的CI系统提供了广泛的语音理解响度范围。除了超过阈值的语音理解外，还应额外注意软语音，因此结果应通过低水平的语音测听来证实。证据等级：2。

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Optimizing CI Systems for Better Recognition of Soft Speech —the Concept of Broad-Range Mapping

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Optimizing CI Systems for Better Recognition of Soft Speech —the Concept of Broad-Range Mapping

Objectives

The individual mapping of cochlear implants (CIs) aims to optimize the user's speech understanding. Recent investigations have shown the importance of soft speech: (1) According to Datalog studies, a large proportion of speech components lies in the range below 60 dB, and (2) soft speech represents a separate category in CI outcome, in addition to supra-threshold speech and speech in noise. Soft-speech understanding can be influenced by optimizing T-values or by global parameters (loudness growth and TSPL in the Nucleus system). This study focussed on improving soft speech below 60 dB by optimizing loudness growth.

Methods

Speech understanding with varying loudness growth in the speech processor CP11 (Cochlear Ltd.) was compared in 20 experienced adult CI users. The mean soft-speech score based on monosyllabic words at 40 and 50 dB was introduced for quantification.

Results

Six of the 20 patients studied showed significant individual improvement for soft speech when loudness growth was optimized, while none showed a significant decrease under quiet or noisy test conditions.

Conclusion

Actual CI systems offer a broad loudness range of speech understanding. In addition to suprathreshold speech understanding, additional attention should be paid to soft speech, and the result should therefore be confirmed by speech audiometry at low levels.