A Survey on Thai Input Methods on Smartphones <s> Word Candidate Ranking <s> This paper introduces an approach to improve Thai text entry on virtual keyboards. We propose a word completion on new keyboard layouts called vowel-separated keyboard layouts. Based on a Thai writing system, all vowels locate only four positions i.e. top, bottom, left and right of a consonant. Thus, we design our keyboard layouts by grouping vowels with the same position together and place the vowel group buttons into four positions of keyboard area. This should reduce the searching time when typing vowels. While all consonants still contain in the middle area and the consonant's arrangement is based on standard Thai layout named Kedmanee layout. We design two type of the vowel-separated layouts i.e. distance-based layout and big-button layout. We compare the performance of the proposed layout with the ordinary layout. Both proposed layouts yield better performance than the ordinary one especially the big-button layout. Most of test subjects prefer to use big-button layout because the layout look more simple and they can easily find the character they want. <s> BIB001 </s> A Survey on Thai Input Methods on Smartphones <s> Word Candidate Ranking <s> This paper presents an approach to improve the correctness for Thai text inputting via virtual keyboard on touch screen mobile phones. The proposed approach is to generate candidate character based on statistical model from bivariate analysis of pre-collected coordinate data and apply the character trigram model to each candidate character sequence. From user's touch positions, a set of candidate characters with high position-based probability is generated. Then, the character trigram model is applied to each generated candidate characters sequence. For each character sequence, a probability is computed from the weighted combination of position-based and character trigram models. In the end, the character sequence with the highest probability is selected to be the most appropriate sequence. Experiments were conducted to compare the typing accuracy between an ordinary Thai virtual keyboard and our proposed algorithm using the same Thai keyboard layout. Results demonstrate that the proposed algorithm provides the improvement in the text entry accuracy in both character levels and word levels. <s> BIB002
After the word candidate generation process, a list of word candidates is constructed. This list will then be shown to a user to select the preferred word. However, due to the number of candidates and the limited space on the touch screen, the candidates must be ranked so that the most probable candidates are displayed to the user. Here are the criteria used to rank the word candidates: Word frequency from standard corpus is a basic feature of word candidates that can be obtained from a corpus. A word that is frequently used in the corpus is assumed to be used frequently in the smartphones. Thus, the word candidates with high frequency are highly ranked. This criteria is used in various input methods BIB001 - BIB002 . However, the criterion has a disadvantage on dealing with unknown words since they cannot be found in the standard corpus. Weighted word frequency from user word list  improves the disadvantage of the word frequency from the corpus by collecting all the words inputted by the user. Then, the word frequency from the standard corpus and the frequency from the user word list are combined and used as a ranking criterion. Thus, the weighted word frequency f w can be computed as: where w represents a word candidate, α is a weighting factor with 0.0 ≤ α ≤ 1.0, f c and f u are the word frequency in the standard corpus and the user-defined word list, respectively. Edit distance represents the difference between the input string and a word candidate. By using this criterion, the word candidate that is more similar to the input string is highly ranked. This criterion is helpful for input methods that do not require the user to input the exact string e.g.  .