Phonetic Mapping Research Articles

L2 Proficiency Level Influences Loanword Adaptation: Variable Adaptation of English Co-occurrence of Low Vowel and Nasal Into Mandarin

As the most commonly established and attested language contact phenomenon, loanwords, also known as lexical borrowings, may undergo transformations when borrowed from the source language (SL) to the borrowing language (BL). Previous studies have separately illustrated the role of perception and phonology in the borrowing process. However, the speech perception or phonology contributes more to the adaptation pattern in some cases than others. Few studies attempt to explain this phenomenon. To fill in the gap, the present study hypothesizes that differences in borrowers’ L2 proficiency level of the SL are the potential source. To examine this hypothesis, an online adaptation experiment was designed and conducted. The experiment examines how Mandarin Chinese native speakers adapt the English non-words ended in the combination of low vowel and nasal coda. The results suggest that BL monolinguals and less proficient L2 learners of the SL tend to use a phonetic mapping strategy guided by the backness of vowels, while advanced learners of the SL are more likely to adopt a phonological mapping strategy based on coda nasal place. This paper concludes by proposing that borrowers’ L2 proficiency level has an effect on the certain randomized variations in the process of loanword adaptation.

Popular Phonetic Mapping in The Qur’an and Its Implications on Teaching Arabic for Non-Native Speakers

The advantages of Arabic as the language of the Qur’an are its variety of sounds in each word with derivations in various forms and meanings. This study aimed to map popular phonetics with repetition rate in the Qur'an in order to build implicative concepts in Arabic learning for non-native speakers. The research used a qualitative approach with the type of literature research. As a preliminary research, data were obtained through documentary techniques from the Qur'an and Surah al-Wāqi'ah was taken as a data sourcebecause it represented the criteria as a popular surah. The analysis used a content analysis approach through the stages of condensation, presentation and conclusions. The results of the study was found that popular phonetics had vocal repetitions of 1,015 short vowels, 246 long vowels and 1,512 consonants. The results showed that the frequency of repetition of both vowels and consonants in the Qur’an had a phonetic sequence pattern from front to back, which was in line with Chomsky’s universal rules and the natural order hypothesis of Krashen. In addition, the results were complemented by the hypothetical presupposition of the implications in Arabic learning for non-native speakers, both linguistically, psychologically, and pedagogically.

Segmentul fonetic inițial ‘pie-’ în pieptene și denumiri pentru pieptene, pe baza ALRR. Sinteză, vol. I

This paper takes a look at the palatalization of initial pie- in pieptene ‘comb’ (noun) based on the answers synthetized in ALRR. Sinteză, vol. I. Twenty-three individual map headers are included in the phonetic map, based on respondents’ first answer given in the regional atlases, added by different variants given as second and/or third answers. While the collocation “palatalization of the labials” may not be the most accurate in describing the discussed phenomena (see cited works), it has been used by virtue of Romanian linguistic tradition. As far as names for the notion of pieptene ‘comb’ are concerned, the entire Daco-Romanian territory (today’s Romania and the Republic of Moldova, where regional atlases have been published) favours the inherited term pieptene, from the Latin accusative pectinem (Lat. pecten, pectinis) over words with different etymologies. Of course, the word pieptene (which is the literary form) shows a great deal of variation both phonologically, and morphologically (change of declension).

DESARROLLAR HABILIDADES PARA LOGRAR UNA CORRECTA PRONUNCIACIÓN EN LOS ESTUDIANTES DE 2DO AÑO DE LENGUAS EXTRANJERAS

The new model of Foreign Languages Department from Las Tunas University for the English language teaching has among their characteristics the differentiated preparation of the students in this level. This research plans to develop abilities to achieve an accurate pronunciation in the students of 2nd year of Foreign Languages. The proposal objective is to elaborate some exercises to give solution to pronunciation problems to achieve the end in the teaching of the foreign language: communication, and therefore, to achieve an excellence social communicator taking into account the social model that society requires. The study done give us a didactic conception for the development of abilities to achieve an accurate pronunciation, with the use of a phonetic map, to become familiar the students with the realization of a sound or sequence of simulated sounds, with the visual experience that give us this teaching aid. Besides, to express recognition and production of the simulated pronunciation in the English language at the word and speech level with reproductive and productive exercises and the listening training in the specific practice; to differentiate the different ways of the English language, specially, the British and North American, thus the students have the possibilities to evaluate the diversity of cultural elements present in the same tongue in many regions of the planet.

Labels facilitate the learning of competing abstract perceptual mappings

Listeners are able to quickly adapt to synthetic speech, even though it contains misleading and degraded acoustic information. Previous research has shown that testing and training on a given synthesizer using only novel words leads listeners to form abstract or generalized knowledge for how that particular synthesizer maps different acoustic patterns onto their pre-existing phonological categories. Prior to consolidation, this knowledge has been shown to be susceptible to interference. Given that labels have been argued to stabilize abstract ideas in working memory and to help learners form category representations that are robust against interference, we examined how learning for a given synthesizer is affected by labeled or unlabeled immediate training on an additional synthesizer, which uses a different acoustic to phonetic mapping. We demonstrated that the learning of an additional synthesizer interferes with the retention of a previously learned synthesizer but that this is ameliorated if the additional synthesizer is labeled. Our findings indicate that labeling may be important in facilitating daytime learning for competing abstract perceptual mappings prior to consolidation and suggests that speech perception may be best understood through the lens of perceptual categorization.

Supervisory Data Alignment for Text-Independent Voice Conversion

We propose new supervisory data alignment methods for text-independent voice conversion which do not need parallel training corpora. Phonetic information is used as a restriction during alignment for mapping the data from the source speaker onto the parameter space of a target speaker. Both linear and nonlinear methods are derived by considering alignment accuracy and topology preservation. For the linear alignment, we consider common phoneme clusters of the source and target space as benchmarks and adapt the source data vector to the target space while maintaining the relative phonetic positions among neighborhood clusters. In order to preserve the topological structure of the source parameter space and improve the stability of conversion and the accuracy of the phonetic mapping, a supervised self-organizing learning algorithm considering phonetic restriction is proposed for iteratively improving the alignment outcome of the previous step. Both the linear and nonlinear methods can also be applied in the cross-lingual case. Evaluation results show that the proposed methods improve the performance of alignment in terms of both alignment accuracy and stability for text-independent voice conversion in intra-lingual and cross-lingual cases.

Normalization of Chinese chat language

Real-time communication platforms such as ICQ, MSN and online chat rooms are getting more popular than ever on the Internet. There are, however, real risks where criminals and terrorists can perpetrate illegal and criminal abuses. This highlights the security significance of accurate detection and translation of the chat language to its stand language counterpart. The language used on these platforms differs significantly from the standard language. This language, referred to as chat language, is comparatively informal, anomalous and dynamic. Such features render conventional language resources such as dictionaries, and processing tools such as parsers ineffective. In this paper, we present the NIL corpus, a chat language text collection annotated to facilitate training and testing of chat language processing algorithms. We analyse the NIL corpus to study the linguistic characteristics and contextual behaviour of a chat language. First we observe that majority of the chat terms, i.e. informal words in a chat text, is formed by phonetic mapping. We then propose the eXtended Source Channel Model (XSCM) for the normalization of the chat language, which is a process to convert messages expressed in a chat language to its standard language counterpart. Experimental results indicate that the performance of XSCM in terms of chat term recognition and normalization accuracy is superior to its Source Channel Model (SCM) counterparts, and is also more consistent over time.

Novel second-language words and asymmetric lexical access

The lexical and phonetic mapping of auditorily confusable L2 nonwords was examined by teaching L2 learners novel words and by later examining their word recognition using an eye-tracking paradigm. During word learning, two groups of highly proficient Dutch learners of English learned 20 English nonwords, of which 10 contained the English contrast /ε/-æ/ (a confusable contrast for native Dutch speakers). One group of subjects learned the words by matching their auditory forms to pictured meanings, while a second group additionally saw the spelled forms of the words. We found that the group who received only auditory forms confused words containing /æ/ and /ε/ symmetrically, i.e., both /æ/ and /ε/ auditory tokens triggered looks to pictures containing both /æ/ and /ε/. In contrast, the group who also had access to spelled forms showed the same asymmetric word recognition pattern found by previous studies, i.e., they only looked at pictures of words containing /ε/ when presented with /ε/ target tokens, but looked at pictures of words containing both /æ/ and /ε/ when presented with /æ/ target tokens. The results demonstrate that L2 learners can form lexical contrasts for auditorily confusable novel L2 words. However, and most importantly, this study suggests that explicit information over the contrastive nature of two new sounds may be needed to build separate lexical representations for similar-sounding L2 words.

Linguistic and Behavioural Studies of Chinese Chat Language

Real-time communication platforms such as ICQ, MSN and online chat rooms are popular today over the Internet. The language used on these platforms differs significantly from standard natural language. Comparatively, this language, referred to as chat language, is informal, anomalous and dynamic. In this paper, the NIL corpus — a Chinese chat language text collection — is presented which is constructed to facilitate language study. Also, linguistic characteristics and ecological behaviour of the language are studied. We show that chat language is anomalous and dynamic in nature leading to the out-of-vocabulary, ambiguity and sparse data problems. To tackle these problems, a novel chat language model is proposed. The model is based on phonetic mapping between chat terms and their standard natural language counterparts.

Experimental Studies Using Statistical Algorithms on Transliterating Phoneme Sequences for English–Chinese Name Translation

Machine transliteration is automatic generation of the phonetic equivalents in a target language given a source language term, which is useful in many cross language applications. Transliteration between far distant languages, e.g. English and Chinese, is challenging because their phonological dissimilarities are significant. Existing techniques are typically rule-based or statistically noisy channel-based. Their accuracies are very low due to their intrinsic limitations on modeling transcription details. We propose direct statistical approaches on transliterating phoneme sequences for English–Chinese name translation. Aiming to improve performance, we propose two direct models: First, we adopt Finite State Automata on a process of direct mapping from English phonemes to a set of rudimentary Chinese phonetic symbols plus mapping units dynamically discovered from training. An effective algorithm for aligning phoneme chunks is proposed. Second, contextual features of each phoneme are taken into consideration by means of Maximum Entropy formalism, and the model is further refined with the precise alignment scheme using phoneme chunks. We compare our approaches with the noisy channel baseline that applies IBM SMT model, and demonstrate their superiority.

Weight-by-position adjunction and syllable structure

Most cross-linguistic variation in weight criteria is attributed to the parameterized application of Weight-by-Position adjunction to codas on a language-specific basis [Linguistic Inquiry 20 (1989) 253]. This paper explores the hypothesis that coda weight is ultimately predictable from syllable structure. An extensive survey of quantity-sensitive stress systems shows that languages that allow a proportionately large set of high sonority codas are far more likely to treat CVC as heavy than languages possessing a proportionately smaller inventory of high sonority codas. This link between coda inventory and coda weight is shown to follow from a model of weight in which syllable structure influences the phonetic map against which potential weight criteria are evaluated on a language-specific basis.

Use of Technology in Phonological Intervention

Microcomputers can support phonological intervention in a variety of ways. Software and hardware can assist clinicians in identifying errors and establishing appropriate treatment targets. Technology can also help to determine the nature of errors so that optimal intervention methods are used. Specific technology tools for addressing phonological errors due to problems with articulation, phonemic identification, and phonetic mapping are discussed. The use of technology to document and analyze treatment performance is also addressed.

An extended Kohonen phonetic map

This letter contains an approach to improve the Kohonen phonetic typewriter [1] by enlarging the phonetic objects which are used to label the phonetic map: the transitions between phonemes are introduced as new labels of neurons.

Neural network feature maps for Chinese phonemes

It has been shown through a number of experiments that neural networks can be used for a phonetic typewriter. Algorithms can be looked on as producing self-organizing feature maps which correspond to phonemes. In the Chinese language the utterance of a Chinese character consists of a very simple string of Chinese phonemes. With this as a starting point, a neural network feature map for Chinese phonemes can be built up. In this paper, feature map structures for Chinese phonemes are discussed and tested. This research on a Chinese phonetic feature map is important both for Chinese speech recognition and for building a Chinese phonetic typewriter.