Department of Otorhinolaryngology, Hannover Medical School, Hannover, Germany.
Department of Behavioral Sciences and Learning, Linnaeus Centre HEAD, Swedish Institute for Disability Research, Department of Behavioral Sciences and Learning, Linköping University, Linköping, Sweden.
Ear Hear. 2021 July/Aug;42(4):846-859. doi: 10.1097/AUD.0000000000001002.
Actively following a conversation can be demanding and limited cognitive resources must be allocated to the processing of speech, retaining and encoding the perceived content, and preparing an answer. The aim of the present study was to disentangle the allocation of effort into the effort required for listening (listening effort) and the effort required for retention (memory effort) by means of pupil dilation.
Twenty-five normal-hearing German speaking participants underwent a sentence final word identification and recall test, while pupillometry was conducted. The participants' task was to listen to a sentence in four-talker babble background noise and to repeat the final word afterward. At the end of a list of sentences, they were asked to recall as many of the final words as possible. Pupil dilation was recorded during different list lengths (three sentences versus six sentences) and varying memory load (recall versus no recall). Additionally, the effect of a noise reduction algorithm on performance, listening effort, and memory effort was evaluated.
We analyzed pupil dilation both before each sentence (sentence baseline) as well as the dilation in response to each sentence relative to the sentence baseline (sentence dilation). The pupillometry data indicated a steeper increase of sentence baseline under recall compared to no recall, suggesting higher memory effort due to memory processing. This increase in sentence baseline was most prominent toward the end of the longer lists, that is, during the second half of six sentences. Without a recall task, sentence baseline declined over the course of the list. Noise reduction appeared to have a significant influence on effort allocation for listening, which was reflected in generally decreased sentence dilation.
Our results showed that recording pupil dilation in a speech identification and recall task provides valuable insights beyond behavioral performance. It is a suitable tool to disentangle the allocation of effort to listening versus memorizing speech.
积极参与对话可能会很费力,并且必须分配有限的认知资源来处理言语、保留和编码感知到的内容,并准备回答。本研究的目的是通过瞳孔扩张来区分努力分配,即将用于听力的努力(听力努力)和用于记忆的努力(记忆努力)区分开来。
25 名听力正常的德语母语者在进行句子结尾词识别和回忆测试时接受了瞳孔测量。参与者的任务是在四说话者背景噪声中听句子,并在之后重复最后一个词。在一系列句子结束后,他们被要求尽可能多地回忆出最后一个词。记录了瞳孔扩张在不同句子长度(三个句子与六个句子)和不同记忆负荷(回忆与不回忆)下的情况。此外,还评估了降噪算法对性能、听力努力和记忆努力的影响。
我们分析了每个句子前的瞳孔扩张(句子基线)以及每个句子相对于句子基线的扩张(句子扩张)。瞳孔测量数据表明,在需要回忆的情况下,句子基线的增加更为陡峭,这表明由于记忆处理,记忆努力更高。这种句子基线的增加在更长列表的后半部分更为明显,即在六个句子的后半部分。在没有回忆任务的情况下,句子基线在列表的过程中下降。降噪似乎对听力努力的分配有显著影响,这反映在句子扩张的普遍减少上。
我们的结果表明,在语音识别和回忆任务中记录瞳孔扩张可以提供比行为表现更有价值的见解。它是一种将努力分配区分用于听力和记忆言语的合适工具。