# An Acoustic Feature-Based Deep Learning Model for Automatic Thai Vowel Pronunciation Recognition
###### Abstract  
For Thai vowel pronunciation, it is very important to know that when mispronunciation occurs, the meanings of words change completely. Thus, effective and standardized practice is essential to pronuncing words correctly as a native speaker. Since the COVID-19 pandemic, online learning has become increasingly popular. For example, an online pronunciation application system was introduced that has virtual teachers and an intelligent process of evaluating students that is similar to standardized training by a teacher in a real classroom. This research presents an online automatic computer-assisted pronunciation training (CAPT) using deep learning to recognize Thai vowels in speech. The automatic CAPT is developed to solve the inadequacy of instruction specialists and the complex vowel teaching process. It is a unique system that develops computer techniques integrated with linguistic theory. The deep learning model is the most significant part of recognizing vowels pronounced for the automatic CAPT. The major challenge in Thai vowel recognition is the correct identification of Thai vowels when spoken in real-world situations. A convolutional neural network (CNN), a deep learning model, is applied and developed in the classification of pronounced Thai vowels. A new dataset for Thai vowels was designed, collected, and examined by linguists. The result of an optimal CNN model with Mel spectrogram (MS) achieves the highest accuracy of 98.61%, compared with Mel frequency cepstral coefficients (MFCC) with the baseline long short-term memory (LSTM) model and MS with the baseline LSTM model have an accuracy of 94.44% and 90.00% respectively. computer-assisted pronunciation training; convolutional neural networks; Thai vowels; speech recognition; mel spectrogram; mel frequency cepstral coefficients +
Footnote †: journal: Medical  
language practice can improve pronunciation skills and helps learners pronounce languages more accurately. Generally, language teachers, specialists, linguists, speech therapists, and native speakers are the people who explain and teach pronunciation to language learners using the listening method. However, because of diverse circumstances between teachers and learners, inaccuracies in judging the appropriateness of pronunciation through hearing are conceivable. The quantity of teachers available is insufficient to meet the needs of all students. A teacher's job is to listen to and correct the mispronunciations of many students throughout the day. As a result, weariness may cause them to lose focus on major information. Furthermore, learners can only perfect their pronunciation in the classroom. Because of the aforementioned limitations, coupled with the situation of the COVID-19 pandemic at present, online learning has become necessary. To solve these problems, an automated system for the intelligent assessment of pronunciation practice is an alternative choice. It can improve the efficiency of the learning process for both learners and teachers because learners are able to study at any location and at any time. Therefore, this research collected recordings of Thai vowels in various environments, for instance at schools, cafeterias, parks, classrooms, bedrooms, and homes, as well as various native speakers in real-world situations, to train the model. With the advancement of information technology and increased computing capabilities, deep learning is increasingly applied for recognition tasks. Deep learning is effective in learning and classification, [2] such as handwritten character recognition and speech recognition. Deep learning is an artificial intelligence (AI) mathematical technique for classification that depends on data using a multilayered neural network. Computer-assisted language learning (CALL) and computer-assisted pronunciation training (CAPT) [3; 4; 5; 6; 7] have gained much attention in the field of language teaching and training. CALL and CAPT systems are widely used to improve language learning and teaching methods.