High variability identification and discrimination training for Japanese speakers learning English /r/-/l/

Second-language (L2) learners can benefit from exposure to phonetically variable speech during computer-based training. Moreover, this training can be effective even for L2 learners who have extensive exposure to their L2 in daily life, suggesting that there is something specific about the training task that aids learning. The present study compared traditional identification training with discrimination training to evaluate whether discrimination training could be effective, and whether different types of focused attention (i.e., on categorization vs. perceptual differences) could combine to provide a greater increase in learning. Adult Japanese speakers were given 10 sessions of identification and discrimination training, with pre/mid/post tests of identification, auditory discrimination, category discrimination, and /r/–/l/ production. The results demonstrated that both identification and discrimination training increased accuracy of Japanese speakers’ perception and production of English /r/–/l/ in similar ways, but that there was little added benefit to using the two training methods in combination. It thus appears that identification and discrimination training have similar effects in second-language learners, as long as both training methods incorporate high variability

Hedging your bets: L2 learners' acquisition of pragmatic devices in academic writing and computer-mediated discourse

This study had two purposes: The first was to investigate the effects of instruction on pragmatic acquisition in writing. In particular, the focus was on the use of hedging devices in the academic writing of learners of English as a second language. The second purpose was to discover whether this training transferred to a less-planned, less-formal, computer-mediated type of writing, namely a Daedalus interaction. Graduate students enrolled in an academic writing class for non-native English-speakers received treatment designed to increase their metapragmatic awareness and improve their ability to use hedging devices. Data were compared to a control group that did not receive the treatment. The treatment group showed statistically significant increases in the use of hedging devices in the research papers and in the computer-mediated discussion

Individual differences in second-language vowel learning

Adults often have difficulty in acquiring non-native vowels especially when the vowel inventories in first (L1) and second language (L2) are very different. However, even when testing L2 groups with similar profiles, there are great individual differences in the perception and production of non-native sounds. Similarly, computer-based training studies of L2 sounds report that improvement after training can range greatly across individuals. This thesis explores possible sources of individual differences in Greek native speakers’ perception and production of Southern British English vowels. Study 1 examined the perceived relationship between English vowels (in /bVb/ and /bVp/ contexts) and Greek vowels along with English vowel discrimination by the same participants. Greek speakers were found to perceive English vowels via both spectral and temporal assimilation to their L1 categories despite the fact that Greek does not use duration in L1 vowel distinctions. Study 2 defined the endpoints for the synthetic vowel continua to be used in Study 3 using a best exemplars experiment. In study 3, Greek speakers from a homogenous population (in terms of L1 background, age of L2 learning, amount and quality of L2 input) were tested on a large test battery before and after receiving 5 sessions of high-variability perceptual training. The test battery examined their perception of natural and synthetic vowels in L1 (Greek) and L2 (English) and their frequency discrimination ability (F2 only) as well as their production of L2 vowels. Group results showed significant improvement in the trainees’ perception of natural L2 vowels and their L2 vowel production. However, large individual differences were evident both before and after training. Vowel processing in L2 was found to relate to individual variability in vowel processing in L1 and, importantly, to frequency discrimination acuity, a finding that favours an auditory processing hypothesis for L1 and L2 speech perception of vowels

A bilingual/L2 hybrid intervention model: combining human and machine intelligences

Most Taiwanese English language learners have been exposed to traditional approaches to acquiring English as a second or foreign language. Studies demonstrate current/traditional teaching practices are not the most effective for struggling English language learners, and the rate of improvement has been limited. Therefore, this study explores current hybrid environments that integrate a combination of advanced computer-assisted technologies that are operated with artificial intelligence technologies to deliver more effective English language teaching, as well as using translanguaging, a current bilingual teaching method, to support the language acquisition process. To push English language teaching and learning to a more effective and efficient level, artificial intelligence-powered tools providing interventional support have been identified as the integral technological innovations to be leveraged with other tools (reading platforms, formative platforms, on-screen share tools, etc.). Specifically, the use of machine translation tools operating with artificial intelligence technologies have been identified in the literature as a vital computer-assisted tool in supporting learners with their English or second language development via translingualism. However, due to the limitations of artificial intelligence in which causality is lacking, machine translation tools operated on artificial intelligence continue to make errors in translation. Therefore, human intervention is needed in facilitating the teaching and learning process by leveraging other intelligent computer-assisted tools, namely writing assistant software and voice recognition/evaluation software, to make the intervention model more effective in the overall language learning process. Hence, combining machine and human intelligences in deploying machine translation tools, as well as other artificial intelligence-operated tools, serves as an integral approach to addressing learning progression limitations and moving the teaching and learning process into a more innovative hybrid zone based on extending the transtheoretical model for hybrid learning in assisting struggling English language learners. This research will explore how humans can interact with machines by training image-bilingual text translation models via Google's Teachable Machine, as well as utilizing other artificial intelligence-powered tools, namely a writing assistant and a voice recognition or evaluation software, to fill the gaps in current literature regarding integrating intelligent computer-assisted tools for English language learning amongst struggling nonnative English speakers in a hybrid learning environment

Service Activity Report/Participants Enrolled in the September 11th Fund's Employment Assistance Program

This report profiles the services received by the 11,393 individuals served through the September 11th Fund's Employment Assistance Program (EAP). The report defines and describes the types of services available to EAP participants, analyzes how the different groups of participants took advantage of the array of services, and shows the similarities and differences among service providers. The report also presents detailed statistical tables on the services received by participants

About training manuals for teaching Russian as a foreign language in the modern educational paradigm

The article is devoted to the solution of the current problems of modern communication and intercultural educational paradigms that center around the consideration of foreign students national specific in teaching Russian at the preparatory course of military school. Specific features of the course are that the language is the central core of training, performing a communicative function, in the process of development of everyday communication skills and abilities, learning of the language for special purposes starts within the first month of training. The development of modern methods of interactive teaching of Russian as a Foreign Language contributes to the use of computer technology, thereby implementing a personality-oriented approach. We use the method of multimedia transformer. The method involves the preparation of a large number of training materials: text files, glossaries, presentation materials, workbooks, reference materials, etc. Development of own training manual is offered as a solution of a set of tasks: to take into account the specifics of the languages and mentalities of foreign military personnel, to give not only language training, but also to help to master subjects of future military occupation. This article describes two training manuals: Russian as a Foreign Language Workbook. Writing. Phonetics. Intonation (Elementary Level) and The Experimental Electronic Multilingual Dictionary of Military Terms. The Workbook is universal, since it is intended to be used in addition to different Russian as a Foreign Language textbooks. The manual consists of three sections (Writing, Phonetics, Intonation). For instance: 1) the second section Phonetics includes 14 units and four of them contain three blocks - for speakers of different languages; 2) for each intonation construction exercises including basic dictionary that is necessary for military personnel were developed. At the moment we have published Russian as a foreign language Workbooks (Writing. Phonetics. Intonation) with tasks translated into English, French and Laotian. We pursue to achieve higher intensity in the process of speaking and writing skills acquisition. Creation of the multilingual vocabulary of military terms is targeted at development of professional competence that provides removal of language barriers in the process of studying military humanitarian and technical sciences by foreigner students. The content of the manuals developed by the teachers of the Novosibirsk Technical University and the Novosibirsk Higher Military Command School is analyzed in terms of implementing nationally and professionally oriented teaching of the Russian language as a foreign language

Language Identification Using Visual Features

Automatic visual language identification (VLID) is the technology of using information derived from the visual appearance and movement of the speech articulators to iden- tify the language being spoken, without the use of any audio information. This technique for language identification (LID) is useful in situations in which conventional audio processing is ineffective (very noisy environments), or impossible (no audio signal is available). Research in this field is also beneficial in the related field of automatic lip-reading. This paper introduces several methods for visual language identification (VLID). They are based upon audio LID techniques, which exploit language phonology and phonotactics to discriminate languages. We show that VLID is possible in a speaker-dependent mode by discrimi- nating different languages spoken by an individual, and we then extend the technique to speaker-independent operation, taking pains to ensure that discrimination is not due to artefacts, either visual (e.g. skin-tone) or audio (e.g. rate of speaking). Although the low accuracy of visual speech recognition currently limits the performance of VLID, we can obtain an error-rate of < 10% in discriminating between Arabic and English on 19 speakers and using about 30s of visual speech

Production of L3 Vowels: Is it Possible to Separate them from L1 and L2 Sounds?

It is incontrovertible that acquisition of a sound system of a second language is always a complex phenomenon and presents a great challenge for L2 learners (e.g. Rojczyk, 2010a). There are numerous studies (e.g. Nowacka, 2010; Flege, 1991) which show that L2 learners whose first language has a scarce number of sounds, have problems to distinguish L2 sound categories and tend to apply their L1 segments to new contexts. It may be easily detectable in the case of vowels. There is abundance of studies examining L2 learners’ successes and failures in production of L1 and L2 vowels (e.g. Flege, 1992; Nowacka, 2010; Rojczyk, 2010a). Usually such projects show how difficult it is for L2 learners to separate “old” and “new” vowel categories. However, the situation becomes much more complicated when we think of third language (L3) production. While in the case of L2 segmental production the number of factors affecting L2 sounds is rather limited (either interference from learners’ L1 or some kind of L2 intralingual influence), in the case of L3 segmental production we may encounter L1→L3, L2→L3 or L3 intralingual interference. This makes separation of L3 sounds a much more complex process. The aim of this study is to examine whether speakers of L1 Polish, L2 English and L3 German are able to separate new, L3 vowel categories from their native and L2 categories. Being a part of a larger project, this time the focus is on German /œ/. This vowel was chosen since it is regarded as especially difficult for Polish learners of German and it is frequently substituted with some other sounds. A group of English philology (Polish-English-German translation and interpretation programme) students was chosen to participate in this project. They were advanced speakers of English who did not encounter any difficulties in communication with native speakers of this language and upper-intermediate users of German. They had been taught both English and German pronunciation/practical phonetics during their studies at the University of Silesia. The subjects were asked to produce words containing analysed vowels, namely: P /u/, P /ɔ/, P /ɛ/, E /u/, E /ɔ / and G /œ/. All examined vowels were embedded in a /bVt/ context. The target /bVt/ words were then embedded in carrier sentences I said /bVt/ this time in English, Ich sag’ /bVt/ diesmal in German and Mówię /bVt/ teraz in Polish, in a non-final position. The sentences were presented to subjects on a computer screen and the produced chunks were stored in a notebook’s memory as .wav files ready for inspection. The Praat 5.3.12 speech-analysis software package (Boersma, 2001) was used to scroll through the audio files in order to locate an onset and offset of target vowels, measure the F1 and F2 frequencies and plot vowels on the plane. All analyses were also performed using Praat. The obtained results shed new light on L3 segmental production and L1 and L2 interference