## 2 Materials and Methods  
### Speech Audometry  
Speech audiometry is a test that evaluates a person's ability to hear and understand speech, providing a detailed assessment of a patient's listening abilities in everyday communication. Unlike pure-tone audiometry, this test measures how clearly a patient can perceive and comprehend actual speech sounds [12]. Speech audiometry is mainly divided into two types. The speech reception threshold (SRT) test evaluates the minimum sound level at which a patient can recognize speech. The audiologist adjusts the intensity of various monosyllabic and polysyllabic words and presents them to the patient, measuring the minimum intensity at which the patient can accurately recognize the words [13,14]. The speech discrimination test (SDT) evaluates how accurately a patient can understand and differentiate the presented speech. This test involves presenting a list of words at various sound levels and measuring how accurately the patient can repeat them [15,16]. Differences in pitch and speaker characteristics can also influence a patient's perception of the SDT, making it helpful for assessing listening abilities in more realistic conversational settings.  
The words used in this process may be pre-recorded or directly spoken by the examiner, and a patient's auditory response can vary based on the pitch or gender of the voice (e.g., male or female voice). For this reason, standardized voices are often used during testing, but in some cases, patients may be exposed to various voices with different pitches and speaking styles to evaluate how they respond to a wider range of speech characteristics [17].  
Speech audiometry is essential for accurately assessing a patient's hearing condition and determining the need for hearing aids or cochlear implants. It is particularly valuable for evaluating listening skills in everyday conversations. Additionally, speech audiometry can be used for various purposes, such as identifying the degree and type of hearing loss, assessing the prognosis of auditory treatments, evaluating the effectiveness of therapy, selecting rehabilitation options, and choosing suitable hearing aids [18].  
Additionally, according to the research paper by [PERSON] et al. [19], a study was conducted to investigate the potential of automating self-administered speech audiometry using automatic speech recognition (ASR) technology. The study's primary objective emphasized that speech audiometry is a crucial tool for evaluating the speech recognition abilities of patients with hearing loss, particularly in assessing how accurately they can recognize speech in noisy environments. The study focused on the SRT test, a form of speech audiometry, and used data from a total of 73 participants. The performance was evaluated using DNN and TDNN systems. Here, DNN refers to a Deep Neural Network, which is composed of multiple layers of neurons used to learn the complex non-linear relationships between input data and output. TDNN stands for Time Delay Neural Network, a neural network capable of processing time-series data by considering time delays, making it particularly effective in analyzing time-dependent changes, such as speech signals.  
This research confirmed the potential of ASR technology to automate speech audiometry, offering a method to improve access to hearing assessments by reducing reliance on expert-administered tests. The findings particularly benefit patients using hearing aids or cochlear implants, providing practical advantages.