# Mouth Sounds: A Review of Acoustic Applications and Methodologies
## 5 Discussion  
### Recording Conditions  
Previous studies providing information on the processing, recording, and analysis of mouth sounds were limited in several aspects. Firstly, it was observed that some studies did not detail their recording conditions [48; 57; 94; 105; 132], pointing out the need for audio experts in these multidisciplinary teams. In [50], the influence of real environments on recorded data was mentioned, as real-life settings may have altered the quality of recordings. In [135], it was suggested that voice data must be collected in a quiet room and assessed in a controlled environment. However, this is extremely difficult for many studies due to the nature of the context, for example, recording cough sounds in a hospital with typical background noise, such as talking, ambulance sirens, and machine noises [63]. Several researchers performed experiments in noisy environments [56; 83; 89; 118] or used non-professional audio equipment, such as cellphones or laptops [10; 43; 48; 61; 68; 69; 78; 88; 89; 93; 94; 96; 114; 96; 118], which could reduce the quality of the data obtained. Only three studies reported recording sounds in acoustically treated rooms [46; 47; 108]. This condition is vital, because treated rooms reduce unwanted reflections or noises in recordings that could alter the original sound, as previously mentioned. Nevertheless, it reduces pathology detection under the noisy conditions present in daily life, which indicates the need for noise-robustness algorithms. The recording conditions and acquisition systems in studies related to neurological condition identification had some other implications. In [89], a built-in microphone from a laptop was used, which could impact the fidelity of audio recordings. The frequency responses of audio devices tend to modify the frequency content of audio signals to the point that they can distort them [136]. In future studies, smartphones with a wide and flatter frequency range should be used to acquire more spectral information about mouth sounds. Still, obtaining suitable recording equipment could be difficult due to its cost [113]. This limitation calls for more accessible devices over which acoustic analyses can be conducted, and using smartphones as a tool for recording audios has proven to be a reliable technique. Microphone selection is crucial for quality audio recordings and, consequently, for analyzing the human voice. According to [83], the most important characteristics to consider on a microphone for voice recording are directionality, transduction, frequency response, and mouth-to-microphone distance. Additionally, iOS devices were compared against a gold-standard computer preamplification system. The results concluded that recordings from the iOS device had no statistically significant difference compared with the gold standard [83]. However, there were limitations, as only healthy subject voices were used, and only one type of iOS device was employed. Further, the distance between microphones and lips varied across studies, ranging from 2.5-50 cm. There was no standardization of the distance, which should be further considered. Close placement of the microphone to the lips could cause the proximity effect [137], which accentuates lower frequencies, having implications when extracting acoustic features. In fact, in [82], it was affirmed that a constant distance between the mouth and the microphone is critical for improving estimation accuracy. Nonetheless, the distance to the mouth varied widely either for the comfort of the subject [65; 68; 70; 87; 89; 113; 114] or for the simulation of the distance between two people [53; 64]. Either way, this separation distance between the mouth and microphone could significantly affect the recorded signal's quality. Several studies standardized the sampling rate of the voice signal to 44.1 kHz and 16-bit depth [46; 47; 48; 70; 112]. Others chose 16 kHz [52; 60; 62; 112] and 22,050 Hz sampling rates at 16 bits [70].