From seen to unseen: Designing keyboard-less interfaces for text entry on the constrained screen real estate of Augmented Reality headsets

Text input is a very challenging task in the constrained screen real-estate of Augmented Reality headsets. Typical keyboards spread over multiple lines and occupy a significant portion of the screen. In this article, we explore the feasibility of single-line text entry systems for smartglasses. We first design FITE, a dynamic keyboard where the characters are positioned depending on their probability within the current input. However, the dynamic layout leads to mediocre text input and low accuracy. We then introduce HIBEY, a fixed 1-line solution that further decreases the screen real-estate usage by hiding the layout. Despite its hidden layout, HIBEY surprisingly performs much better than FITE, and achieves a mean text entry rate of 9.95 words per minute (WPM) with 96.06% accuracy, which is comparable to other state-of-the-art approaches. After 8 days, participants achieve an average of 13.19 WPM. In addition, HIBEY only occupies 13.14% of the screen real estate at the edge region, which is 62.80% smaller than the default keyboard layout on Microsoft Hololens.Peer reviewe

Design and Evaluation of Controller-based Raycasting Methods for Efficient Alphanumeric and Special Character Entry in Virtual Reality

Alphanumeric and special characters are essential during text entry. Text entry in virtual reality (VR) is usually performed on a virtual Qwerty keyboard to minimize the need to learn new layouts. As such, entering capitals, symbols, and numbers in VR is often a direct migration from a physical/touchscreen Qwerty keyboard—that is, using the mode-switching keys to switch between different types of characters and symbols. However, there are inherent differences between a keyboard in VR and a physical/touchscreen keyboard, and as such, a direct adaptation of mode-switching via switch keys may not be suitable for VR. The high flexibility afforded by VR opens up more possibilities for entering alphanumeric and special characters using the Qwerty layout. In this work, we designed two controller-based raycasting text entry methods for alphanumeric and special characters input (Layer-ButtonSwitch and Key-ButtonSwitch) and compared them with two other methods (Standard Qwerty Keyboard and Layer-PointSwitch) that were derived from physical and soft Qwerty keyboards. We explored the performance and user preference of these four methods via two user studies (one short-term and one prolonged use), where participants were instructed to input text containing alphanumeric and special characters. Our results show that Layer-ButtonSwitch led to the highest statistically significant performance, followed by Key-ButtonSwitch and Standard Qwerty Keyboard, while Layer-PointSwitch had the slowest speed. With continuous practice, participants' performance using Key-ButtonSwitch reached that of Layer-ButtonSwitch. Further, the results show that the key-level layout used in Key-ButtonSwitch led users to parallel mode switching and character input operations because this layout showed all characters on one layer. We distill three recommendations from th results that can help guide the design of text entry techniques for alphanumeric and special characters in VR

Optimizing Human Performance in Mobile Text Entry

Although text entry on mobile phones is abundant, research strives to achieve desktop typing performance "on the go". But how can researchers evaluate new and existing mobile text entry techniques? How can they ensure that evaluations are conducted in a consistent manner that facilitates comparison? What forms of input are possible on a mobile device? Do the audio and haptic feedback options with most touchscreen keyboards affect performance? What influences users' preference for one feedback or another? Can rearranging the characters and keys of a keyboard improve performance? This dissertation answers these questions and more. The developed TEMA software allows researchers to evaluate mobile text entry methods in an easy, detailed, and consistent manner. Many in academia and industry have adopted it. TEMA was used to evaluate a typical QWERTY keyboard with multiple options for audio and haptic feedback. Though feedback did not have a significant effect on performance, a survey revealed that users' choice of feedback is influenced by social and technical factors. Another study using TEMA showed that novice users entered text faster using a tapping technique than with a gesture or handwriting technique. This motivated rearranging the keys and characters to create a new keyboard, MIME, that would provide better performance for expert users. Data on character frequency and key selection times were gathered and used to design MIME. A longitudinal user study using TEMA revealed an entry speed of 17 wpm and a total error rate of 1.7% for MIME, compared to 23 wpm and 5.2% for QWERTY. Although MIME's entry speed did not surpass QWERTY's during the study, it is projected to do so after twelve hours of practice. MIME's error rate was consistently low and significantly lower than QWERTY's. In addition, participants found MIME more comfortable to use, with some reporting hand soreness after using QWERTY for extended periods

Chinese Text Entry with Mobile Devices

Tietokoneiden ja nykyaikaisten matkapuhelimien käytön kannalta on olennaista, että niihin voidaan syöttää tekstiä tehokkaasti. Kiinan kielen eri murteita puhuu äidinkielenään noin viidesosa maailman väestöstä eli yli miljardi ihmistä. Kiinan kielen merkki- ja tavuperustaisuus tekee siitä tekstinsyötön kannalta ainutlaatuisen haastavan. Monet kiinalaisista merkeistä ovat rakenteeltaan monimutkaisia ja homofonisia (ääntyvät samalla tavoin) joidenkin muiden merkkien kanssa. Syötettäessä tekstiä näppäimistöltä tavallinen tapa on käyttää ns. pinyin-koodeja, joiden avulla kukin kiinan merkki voidaan esittää useasta latinalaisen aakkoston merkistä koostuvana koodina. Homofoniasta johtuen tarkoitettu kiinan kielen merkki joudutaan tämän jälkeen vielä valitsemaan usean vaihtoehdon joukosta, mikä tekee tekstinsyöttöprosessista vaikeampaa kuin romaanisten kielten tapauksessa. Lisäksi on otettava huomioon Kiinan eri osissa puhutut useat murteet. Kaikki nämä tekijät yhdessä tekevät kiinankielisen tekstin syötöstä tietokoneille haastavaa. Tämän väitöskirjan tavoitteena on parantaa kiinankielisen tekstin syöttötapojen käyttäjäkokemusta käytettäessä matkapuhelimia ja muita mobiililaitteita. Väitöskirjassa tutkitaan empiiristen kokeiden ja mallinnuksen avulla uusia tekstinsyöttötapoja ja niiden käyttöä. Tutkimuksen kohteena on neljä erilaista tekstinsyöttötapaa: kiinankielen käsinkirjoituksen tunnistus, pyörivän kiekon avulla tapahtuva tekstinsyöttö, mandariinikiinaan perustuva sanelu, ja numeronäppäinten avulla tapahtuva pinyin-koodien syöttö. Työssä ehdotetaan uusia tekniikoita sekä käsinkirjoituksen tunnistukseen että kiekkoa käyttävään pinyin-koodien syöttöön. Empiirisissä kokeissa osoittautui että käyttäjät pitivät uusista tekniikoista. Mandariinikiinalle on suunniteltu lyhytviestien sanelusovellus, josta on tehty kaksi käyttäjäkoetta. Myös numeronäppäinten avulla tapahtuvaa pinyin-koodien syöttöä on tutkittu kahdessa kokeessa. Ensimmäisessä kokeessa vertailtiin viittä eri menetelmää. Se tuotti suunnitteluohjeita etenkin koskien fraasien (useamman merkin kokonaisuuksien) syöttöä, tekniikkaa joka voi nopeuttaa tekstinsyöttöä. Toisen osatutkimuksen tuloksena on tekstinsyöttöä kuvaava malli, jonka avulla voidaan ennustaa menetelmän nopeutta kun syötettäessä ei tehdä virheitä. Tutkimus johti myös useisiin jatkotutkimuskysymyksiin. On tarpeen kehittää tehokkaampia menetelmiä tilanteeseen, jossa merkki joudutaan valitsemaan useista vaihtoehdoista. Kehityspotentiaalia on myös merkkien perustana olevien viivojen tunnistustavoissa sekä kosketusnäytöllä esitettyjen näppäimistöjen paremmassa hyödyntämisessä.For using computers and modern mobile phones it is essential that there are efficient methods for providing textual input. About one fifth of the world´s population, or over one billion people, speaks some variety of Chinese as their native language. Chinese has unique characteristics as a logosyllabic language. For example, many Chinese characters are complex in structure and normally homophonic with some others. With keyboards and other key-based input devices the normal approach is to use so-called pinyin input, where the Chinese characters are entered using their pinyin mark that consists of several characters in the Roman alphabet. Because of homophony this technique requires choosing the correct Chinese character from a list of posssible choices, making the input process more complicated than in Roman languages. Moreover, the many varieties of the language in different parts of China have to be taken into account as well. All above factors bring new challenges to the design and evaluation of Chinese text entry methods in computing systems. The overall objective of this dissertation is to improve user experience of Chinese text entry on mobile devices. To achieve the goal, the author explores new interaction solutions and patterns of user behavior in the Chinese text entry process with various approaches including empirical studies and performance modeling. The work covers four means of Chinese text entry on mobile devices: Chinese handwriting recognition, Chinese indirect text entry with a rotator, Mandarin dictation, and Chinese pinyin input methods with a 12-key keypad. New design solutions for Chinese handwriting recognition and pinyin methods utilizing a rotator are proposed and proved being well accepted by users with empirical studies. A Mandarin short message dictation application for mobile phones is also presented , with two associated studies on human factors. Two studies were also carried out on Chinese pinyin input methods that are based on the 12-key keypad. The comparative study of five phrasal pinyin input methods led to design guidelines for the advanced feature of phrasal input. The second study of pinyin input methods produced a predictive model addressing users´ error-free speeds. Based on the conclusions from studies in this thesis, several additional research questions were identified for the future. For example, improvements are necessary to promote user performance on target selection process in Chinese text entry on mobile devices. Moreover, design and studies on stroke methods and Chinese specific soft keyboards are also required

Onsetsu hyoki no kyotsusei ni motozuita Ajia moji nyuryoku intafesu ni kansuru kenkyu

制度:新 ; 報告番号:甲3450号 ; 学位の種類:博士(国際情報通信学) ; 授与年月日:2011/10/26 ; 早大学位記番号:新577

Beginners Performance with MessagEase and QWERTY

With the increased use of mobile phones, interest in text entry with them has also amplified. Many new mobile phones are equipped with a QWERTY keypad; new methods to surpass the QWERTY performance are also being developed. This thesis compares user performance of virtual QWERTY keypad to MessagEase. MessagEase uses 9 keys and can therefore be used even on very small touch displays. 9 characters are entered with tapping and the rest with a tap-and-slide gesture. An experiment was conducted with 10 participants transcribing text with both text entry techniques. The experiment consisted of three sessions. In each session, the participants transcribed 30 phrases in total - 15 phrases using each text entry technique. Responses to the System Usability Scale (SUS) for each text entry technique and informal interview data were also collected. From a Repeated-measures analysis of variance a significant effect of the text entry method on text entry rate was seen (F1,19= 47.140, p < 0.0001). The effect of the session (i.e. learning) was also statistically significant (F2,18= 3.631, p = 0.047).The interaction of the session and method was also statistically significant (F2,18= 10.286, p = 0.001) indicating different learning rates. Average text entry speed with MessagEase was 7.43 words per minute (wpm) in the first session and 10.96 wpm in the third session. Likewise, text entry speed with the QWERTY soft keyboard was 17.75 wpm in the first session and 17.16 wpm in the third session. No significant difference was found in the error rates. Keywords: text entry method, MessagEase, QWERT