# A Web Service for Evaluating the Level of Speech in Korean
###### Abstract  
Speaking is a way for humans to communicate with others using language. The ability to speak according to the speaker is very diverse. In general, language skills improve as intelligence improves. Therefore, it is known that the analysis of a speaker's utterances is a good tool to evaluate the intellectual maturity of the speaker. Until recently, these evaluations have been done manually based on the experience of a handful of experts, but this approach is not only time consuming and costly, but also highly subjective. In this paper, we propose a Korean automatic speech analysis system based on Natural Language Processing (NLP) and web service to solve this problem. For this study, we constructed a web service based on Django to respond to the requests of various users. When a user delivered a transcription file of utterances to the server via the web, the server analyzed the speech ability of the speaker based on various indicators. The server compared the transcription file with the language ability indicators of persons of the same age as the speaker and displayed the result immediately to the user. In this study, we used KoNLPy, a Korean language-processing tool. The automatic speech analysis service analyzed not only the overall language ability of the speaker but also individual domains such as sentence completion ability and vocabulary ability. In addition, a faster and immediate service was made possible without sacrificing accuracy as compared to human analysis. Keywords:Korean speech analysis; web service; language evaluation; Django +
Footnote †: journal: Medical  
with respect to subjects in infancy and childhood. Recently research about the language development of adults and seniors has grown. However, there is no research on the entire age range. Two methods are used for analyzing utterances: the first involves experts who analyze the results by hand, whereas the second uses an automatic analysis system equipped with software technology such as Natural Language Processing (NLP). The first method has been used by a few experts [8], who analyze the utterances based on their experience and assess verbal skills. This type of analysis is not only time consuming and costly, but it is also difficult to be objective. This is because the results analyzed by the experts involve much personal experience and varied opinions as well as established rules. To overcome these drawbacks, a second method has recently been adopted more frequently [9]. An automated analysis system equipped with software technology is a method of analyzing human language based on natural language processing. In English-speaking countries, active research studies are being carried out on automatic analysis systems, but there are few research studies about Korean language. At first, Korean Computerized Language Analysis (KCLA) was developed as a Korean automatic analysis system, followed by the development of Korean Language Analysis (KLA). However, these systems are little different from manual analysis, except that they work on a computer [10; 11]. To overcome these drawbacks, KSTARS was recently developed [12]. KSTARS provides automatic analysis of the word frequency and type of morphemes and words. Compared to KLA, KSTARS differs in that it performs morphological analysis automatically, but its analysis is still limited to subjects in infancy between 2 and 5 years old. Considering that language development continues through all ages, the limitations of KSTARS are clear. In speech pathology, the language of a speaker is generally compared to the language of persons from the same age group to determine a language disorder, based on whether it is within the normal range [13]. However, since KSTARS provides only the number of words or the frequency of morphemes, its disadvantage is that it is difficult to easily discriminate between language disorders or language development degree. In this paper, we propose a Korean automatic spoken analysis system that overcomes the problems mentioned above.