## 4 Discussion
becomes particularly apparent when visual cues from the speaker are present, creating a temporal mismatch between auditory and visual inputs. This incongrurity may strain working memory capacity during noisy listening conditions, as listeners must reconcile limited acoustic information with potentially conflicting visual cues. Such cognitive demands can delay speech comprehension and increase processing load during ongoing communication. These results have potential clinical and research implications. Using Roger and smartphone-based RM is beneficial in reducing the challenges caused by noise relative to not using any device across the SNR and noise types, with benefits of 17.95, 15.39, and 4.11% in Roger, AP NC + LL, and AP TP + LL, respectively. Considering the current device setting is mainly for those without hearing loss, such benefits can potentially help improve hearing difficulties in noise for listeners with TH, occupying 12-15% of the general population [1; 2]. The benefits of the Roger RM system were confirmed by [PERSON] et al. [9] in 10 subjects with TH despite using different Roger transmitters (Pen, Select) and receivers (Roger Focus-first generation). Similar to the RM system, the benefits of using smartphone-based RM on speech recognition in noise are expected in humans with TH. It is also of possible benefit to those who have hearing aids that connect to smartphones when using a remote mic app on the phone, if the Bluetooth delay can be tolerated. However, many HA manufacturers do offer proprietary RM devices now with personal hearing technology. In addition, an iPhone and the AP can work as a portable RM system in daily communication for listeners with TH. This is similar to the findings in Table 1 on the benefit of using the AP as a hearing assistance device [21; 22; 23; 24; 25; 26]. Given the widespread adoption and convenience of smartphones and earbuds, along with the lower cost compared to Roger devices, smartphone-based RM systems can be considered as alternative RM systems for TH individuals with hearing difficulties in noise, particularly those concerned about cost or the stigma associated with traditional hearing devices. Additionally, with the governmental approval of the software for iPhones to adjust the AP for persons with mild-to-moderate hearing impairments, such systems may function both as RM systems and as hearing assistive devices. However, further research on humans is required before these solutions can be suggested as part of clinical protocols. Using VTT and KEMAR has the potential to provide objective verification of new technological features, especially in situations where real participants are unavailable due to constraints such as COVID-19 or lack of funding. This approach can yield objective results that are not influenced by human factors such as age, gender, emotional status, personality, cognitive functions, etc. However, to ensure comparability across different studies, the version of the transcription application (e.g., Otter) should be specified, given the rapid pace of feature development in this high-tech era. Although the results suggested a promising testing method for research and highlighted the potential benefits of using RM for listeners with TH, there are limitations to consider. Firstly, the use of KEMAR may restrict the applicability of the results to humans. Further research involving human participants with various profiles (e.g., age, cognition, and hearing status) is necessary to validate these findings before adopting such a smartphone-based RM system for rehabilitative solutions. Secondly, only one smartphone-based RM system using an iOS device and a single type of headphone was evaluated. This limitation restricts the generalizability of the results to other smartphone platforms (e.g., Android) and different headphones with similar features like LL. Finally, while the cost of an iPhone and the AP may be lower than that of a sophisticated Roger system, these devices may still be expensive for individuals, especially if they are not iPhone users.