Journal articles: 'Mispronunciation'

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Bernier, Dana E., and Katherine S. White. "Toddlers Process Common and Infrequent Childhood Mispronunciations Differently for Child and Adult Speakers." Journal of Speech, Language, and Hearing Research 62, no. 11 (November 22, 2019): 4137–49. http://dx.doi.org/10.1044/2019_jslhr-h-18-0465.

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Purpose This study examined toddlers' processing of mispronunciations based on their frequency of occurrence in child speech and the speaker who produced them. Method One hundred twenty 22-month-olds were assigned to 1 of 4 conditions. Using the intermodal preferential looking paradigm, toddlers were shown visual displays containing 1 familiar object and 1 novel object, labeled by either a child or an adult. Familiar objects were labeled correctly or with a small mispronunciation that is either common in child speech (e.g., waisin for raisin) or infrequent (e.g., rauter for water). Results A significant interaction of speaker and type of mispronunciation showed that, for the child speaker, toddlers treated common and infrequent mispronunciations similarly, with equivalently sized mispronunciation penalties relative to correctly pronounced labels. In contrast, for the adult speaker, toddlers showed a large penalty for common mispronunciations, but infrequent mispronunciations were treated equivalently to correct pronunciations. Conclusion These results both reinforce and extend previous work on toddlers' processing of mispronunciations by revealing a complex interplay of speaker, type of mispronunciation, and specific contrast in toddlers' perceptions of mispronunciations.

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MANI, NIVEDITA, and KIM PLUNKETT. "Does size matter? Subsegmental cues to vowel mispronunciation detection." Journal of Child Language 38, no. 3 (November 1, 2010): 606–27. http://dx.doi.org/10.1017/s0305000910000243.

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ABSTRACTChildren look longer at a familiar object when presented with either correct pronunciations or small mispronunciations of consonants in the object's label, but not following larger mispronunciations. The current article examines whether children display a similar graded sensitivity to different degrees of mispronunciations of the vowels in familiar words, by testing children's sensitivity to 1-feature, 2-feature and 3-feature mispronunciations of the vowels of familiar labels: Children aged 1 ; 6 did not show a graded sensitivity to vowel mispronunciations, even when the trial length was increased to allow them more time to form a response. Two-year-olds displayed a robust sensitivity to increases in vowel mispronunciation size, differentiating between small and large mispronunciations. While this suggests that early lexical representations contain information about the features contributing to vocalic identity, we present evidence that this graded sensitivity is better explained by the acoustic characteristics of the different mispronunciation types presented to children.

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Donselaar, Wilma van. "Mispronunciation Detection." Language and Cognitive Processes 11, no. 6 (December 1996): 621–28. http://dx.doi.org/10.1080/016909696387024.

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Schmid, Peggy M., and Grace H. Yeni-Komshian. "The Effects of Speaker Accent and Target Predictability on Perception of Mispronunciations." Journal of Speech, Language, and Hearing Research 42, no. 1 (February 1999): 56–64. http://dx.doi.org/10.1044/jslhr.4201.56.

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This study makes use of a listening for mispronunciation task to examine how native English listeners perceive sentences produced by non-native speakers. The effects of target predictability and degree of foreign accent were investigated. Native and non-native speakers produced English sentences containing mispronunciation. Mispronunciations (MPs) were constructed by changing the initial phoneme of target words by a single distinctive feature along the dimensions of voicing, place, or manner. Results showed that listeners (a) were more accurate and faster in detecting MPs produced by native than non-native speakers, (b) were more accurate and faster in detecting MPs in predictable than unpredictable sentences, and (3) were more accurate in detecting MPs produced by non-native speakers with milder accents, as compared to heavier accents. These findings suggest that listening to fairly intelligible but accented speech requires increased processing effort—possibly because of subtle differences in intelligibility and increased variability characteristic of non-native speech.

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Zhang, Ying Shan Doris, and Kimberly Noels. "The Frequency and Importance of Accurate Heritage Name Pronunciation for Post-Secondary International Students in Canada." Journal of International Students 11, no. 3 (June 15, 2021): 608–27. http://dx.doi.org/10.32674/jis.v11i3.2232.

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International students’ names are often mispronounced, and this experience can have psychological and relational implications for some students’ cross-cultural adjustment. Little research, however, has examined why students are or are not bothered by mispronunciations. This study examined the impact of heritage name mispronunciation on 173 language-minority international students in Canada. The results indicated that although heritage name mispronunciations occurred frequently, only about half of the sample perceived correct pronunciation as important. Those who felt accurate pronunciation was important stressed that their name had a strong connection to their heritage and that mispronunciations were disrespectful of that significance. Those who felt accurate pronunciation was not important cited little personal connection to the name and accepted mispronunciations for reasons of efficiency. The findings suggest that accurate heritage name pronunciation can facilitate the adjustment of international students by fostering positive affect, communicative comfort, and relational closeness during cross-cultural interactions in the host countries.

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van der Feest, Suzanne V. H., and Paula Fikkert. "Building phonological lexical representations." Phonology 32, no. 2 (August 2015): 207–39. http://dx.doi.org/10.1017/s0952675715000135.

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This paper contributes to the ongoing debate on how much detail young children's word representations contain. We investigate early representations of place of articulation and voicing contrasts, inspired by previously attested asymmetrical patterns in children's early word productions. We tested Dutch-learning 20- and 24-month-olds’ perception of these fundamentally different contrasts in a mispronunciation-detection paradigm. Our results show that different kinds and directions of phonological changes yield different effects. Both 20- and 24-month-olds noticed coronal mispronunciations of labials, but not vice versa. The 24-month-olds noticed voiced mispronunciations of voiceless stops, but not vice versa, while the 20-month-olds failed to notice any voicing mispronunciations. We argue that early lexical representations are specified in very systematic ways, that not all phonological contrasts are encoded at the same time and that the phonological system of a language determines which contrasts are specified first in the representations of early words.

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RAMON-CASAS, MARTA, CHRISTOPHER T. FENNELL, and LAURA BOSCH. "Minimal-pair word learning by bilingual toddlers: the Catalan /e/-/ɛ/ contrast revisited." Bilingualism: Language and Cognition 20, no. 3 (November 18, 2016): 649–56. http://dx.doi.org/10.1017/s1366728916001115.

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Twelve-month-old bilingual and monolingual infants show comparable phonetic discrimination skills for vowels belonging to their native language/s. However, Catalan–Spanish bilingual toddlers, but not Catalan monolinguals, appear insensitive to a vowel mispronunciation in familiar words involving the Catalan–Specific /e/-/ɛ/ contrast. Here bilingual and monolingual toddlers were tested in a challenging minimal-pair word learning task involving that contrast (i.e., [bepi]-[bɛpi]). Both groups succeeded, suggesting that bilinguals can successfully use their phonetic categories to phonologically encode novel words. It is argued that bilinguals’ impoverished vowel representations in familiar words might be the result of experiential input factors (e.g., cognate words and mispronunciations due to accented speech).

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Shufang, Zhang. "Design of an Automatic English Pronunciation Error Correction System Based on Radio Magnetic Pronunciation Recording Devices." Journal of Sensors 2021 (December 27, 2021): 1–12. http://dx.doi.org/10.1155/2021/5946228.

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In this paper, a system for automatic detection and correction of mispronunciation of native Chinese learners of English by speech recognition technology is designed with the help of radiomagnetic pronunciation recording devices and computer-aided software. This paper extends the standard pronunciation dictionary by predicting the phoneme confusion rules in the language learner’s pronunciation that may lead to mispronunciation and generates an extended pronunciation dictionary containing the standard pronunciation of each word and the possible mispronunciation variations, and automatic speech recognition uses the extended pronunciation dictionary to detect and diagnose the learner’s mispronunciation of phonemes and provides real-time feedback. It is generated by systematic crosslinguistic phonological comparative analysis of the differences in phoneme pronunciation with each other, and a data-driven approach is used to do automatic phoneme recognition of learner speech and analyze the mapping relationship between the resulting mispronunciation and the corresponding standard pronunciation to automatically generate additional phoneme confusion rules. In this paper, we investigate various aspects of several issues related to the automatic correction of English pronunciation errors based on radiomagnetic pronunciation recording devices; design the general block diagram of the system, etc.; and discuss some key techniques and issues, including endpoint detection, feature extraction, and the system’s study of pronunciation standard algorithms, analyzing their respective characteristics. Finally, we design and implement a model of an automatic English pronunciation error correction system based on a radiomagnetic pronunciation recording device. Based on the characteristics of English pronunciation, the correction algorithm implemented in this system uses the similarity and pronunciation duration ratings based on the log posterior probability, which combines the scores of both, and standardizes this system scoring through linear mapping. This system can achieve the purpose of automatic recognition of English mispronunciation correction and, at the same time, improve the user’s spoken English pronunciation to a certain extent.

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Buditama, JK Aditya Christya, Catur Atmaji, and Agfianto Eko Putra. "Deteksi Kesalahan Pengucapan Huruf Jawa Carakan dengan Jaringan Syaraf Tiruan Perambatan Balik." IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) 11, no. 2 (October 31, 2021): 155. http://dx.doi.org/10.22146/ijeis.53437.

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Javanese is an Indonesian culture which needs to be preserved, but many Javanese students make mistakes in the pronunciation of Javanese letters and find it difficult to analyze errors by human teachers because of the limited time and subjective assessment, so a system is needed to detect incorrect pronunciation of Javanese letters. Mispronunciation detection system has been widely applied in foreign languages, but the system has not been implemented for Javanese carakan letters. This research develops the Javanese letters mispronunciation detection system using Back-Propagation Artificial Neural Networks (BP-ANN). The dataset is obtained from the recorded pronunciation of hanacaraka texts by 24 speakers with 5 repetitions. ALNS method then used to automatically segment the signal into syllables. ANN-PB use statistical value of Mel-Frequency Cepstral Coefficient (MFCC) method with 7 and 14 coefficients. 10-Fold Cross Validation is used to validate and test the system. The Javanese mispronunciation detection using 7MFCC coefficients produces the highest accuracy of 80,07%. While the Javanese mispronunciation detection using 14 MFCC coefficients produces an accuracy of 82.36% at the highest.

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Ambalegin, Ambalegin, and Fasaaro Hulu. "EFL LEARNERS’ PHONOLOGICAL INTERFERENCE OF ENGLISH ARTICULATION." JURNAL BASIS 6, no. 2 (October 26, 2019): 145. http://dx.doi.org/10.33884/basisupb.v6i2.1415.

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This research investigated the mispronunciation of Putera Batam University EFL learners by adapting the standard of Received Pronunciation (RP) and the factors of English vowels and consonants mispronunciation. This descriptive qualitative research applied observational method with participatory technique in collecting data, and articulatory identity method in analyzing the data. The English mispronunciation was found in the EFL learners’ English pronunciation. The consonant sounds /ð/, /θ/, /th/, /z/, /r/, /ʃ/, /ʧ/, /ʤ/, /nj/, and consonant-closed syllable sound of /k/ were pronounced incorrectly. The consonant sound /ð/ was pronounced as /d/, /θ/ as /t/, /th/ as /t/, /z/as /ɉ/, /r/ as /ɾ/, /ʃ/ as /s/, /ʧ/ as /s/, /ʤ/ as /d/, and /nj/ is pronounced as /ɲ/. Consonant-closed syllable sound of /k/ is articulated as /Ɂ/. The vowel sounds /ə/ and /æ/ were pronounced incorrectly as /e/ and the diphthong sound /eɪ/ were pronounced incorrectly as /e/. These mispronunciation phenomena were caused by some factors based on their background. The factors were; the mother tongue interference (native language), the differences between Indonesian and English sound systems (phonetic ability), the educational background, and the environmental background (amount of exposure).

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Rethinasamy, Souba, Cecilia Xin-Li Chen, and Ruey Shing Soo. "The Influence of Educational Background on Malaysian Chinese Learners’ Mispronunciation of /l/ and /r/." World Journal of English Language 13, no. 1 (December 25, 2022): 303. http://dx.doi.org/10.5430/wjel.v13n1p303.

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Maintaining intelligibility among interlocutors while communicating in English remains a challenging task for many second or foreign language learners. This problem is attributable to many reasons, including learners’ obstacles with pronunciation. The recurring report of Chinese learners having incomprehensible pronunciation of /l/ and /r/ in English words has engendered debate on various factors underlying the problem. Despite the extensive discussion of this issue, previous studies had overlooked educational background as a potential factor which could affect learners’ pronunciation. Thus, this study investigated mispronunciations of /l/ and /r/ among Malaysian Chinese undergraduates vis-à-vis their educational background, namely Chinese-educated (CE) and non-Chinese educated (NCE). The study objectives were to determine CE and NCE learners’ frequency of mispronunciation of English words containing /l/ and /r/ according to phoneme, phoneme position, and mispronunciation characteristics. To this end, a quantitative approach was employed to conduct the study. For data collection, two pronunciation word lists covering /l/ and /r/ in initial, medial, and final positions were provided to 20 CE and NCE undergraduates respectively for assessment purposes. The participants’ pronunciations were recorded, transcribed and transformed into numerical data. The results of the study reveal that Chinese-educated Malaysian undergraduates tend to mispronounce English words containing /l/ in medial and final positions. Furthermore, words containing /l/ in the medial position tend to be substituted; while words with /l/ in the final position tend to be deleted or vocalized by the students. The findings of this study provide valuable insights into the teaching and learning of English pronunciation.

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Nazir, Faria, Muhammad Nadeem Majeed, Mustansar Ali Ghazanfar, and Muazzam Maqsood. "An Arabic Mispronunciation Detection System Based on the Frequency of Mistakes for Asian Speakers." April 2021 40, no. 2 (April 1, 2021): 279–97. http://dx.doi.org/10.22581/muet1982.2102.03.

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Over the last few decades, the field of artificial intelligence and machine learning has evolved. Due to the advancement in these fields, much work has been done to assist language learning with the help of computers called Computer-Assisted Language Learning (CALL). Mispronunciation detection is one of the significant tasks of the CALL system. An efficient mispronunciation detection model has a positive impact on the life of second language learners by providing phoneme level feedback. In this paper, we introduce the phone grouping technique for mispronunciation detection that is based on mistakes probability. We consider mispronunciation detection as a classification problem, traditionally for this purpose, a separate classifier is trained for each phoneme mistake that requires a lot of memory and time. Instead of training a separate classifier, we group the phoneme based on their mistakes probability that helps in reducing the number of the classifiers to be trained and also saves memory and time. We use the Support Vector Machine (SVM) classifier and test the results on the Arabic dataset (28 Phonemes). The performance of our proposed method is evaluated by using accuracy. The results of the model are evaluated using the confusion matrix and gives an accuracy of 88%. Our approach outperforms the existing systems developed for Arabic phonemes in terms of accuracy and is also time/memory efficient.

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SIMON, ELLEN, MATTHIAS J. SJERPS, and PAULA FIKKERT. "Phonological representations in children's native and non-native lexicon." Bilingualism: Language and Cognition 17, no. 1 (March 1, 2013): 3–21. http://dx.doi.org/10.1017/s1366728912000764.

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This study investigated the phonological representations of vowels in children's native and non-native lexicons. Two experiments were mispronunciation tasks (i.e., a vowel in words was substituted by another vowel from the same language). These were carried out by Dutch-speaking 9–12-year-old children and Dutch-speaking adults, in their native (Experiment 1, Dutch) and non-native (Experiment 2, English) language. A third experiment tested vowel discrimination. In Dutch, both children and adults could accurately detect mispronunciations. In English, adults, and especially children, detected substitutions of native vowels (i.e., vowels that are present in the Dutch inventory) by non-native vowels more easily than changes in the opposite direction. Experiment 3 revealed that children could accurately discriminate most of the vowels. The results indicate that children's L1 categories strongly influenced their perception of English words. However, the data also reveal a hint of the development of L2 phoneme categories.

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Zain, Dodi Siraj Muamar, and Titi Wahyukti. "Pelatihan Membaca Simbol Phonetiks dengan Kamus Oxford Sebagai Upaya Peningkatan Akurasi Pengucapan dalam Bahasa Inggris." Jurnal ABDINUS : Jurnal Pengabdian Nusantara 2, no. 1 (July 17, 2018): 62. http://dx.doi.org/10.29407/ja.v2i1.11941.

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Mistakes and errors in pronunciation will affect meaning distribution of certain words. In other words, one might have different interpretation for a certain message because of mispronunciation. In communication using English, pronunciation issues are mostly triggered by irregularity of letters’ pronunciation in which the sounds might be different from the letters. It surely becomes a hindrance in classroom English learning. The use of Oxford dictionary employing phonetiks symbols can be an alternative to overcome mispronunciation problems. Different from common Indonesian-English dictionary, its contents are entirely presented in English. It offers certain challenges to students. Besides, students must also be able to read phonetiks symbols in order to pronounce words appropriately. This Community Service is aimed at introducing oxford dictionary as well as training students to read phonetiks symbols which are the reference in pronouncing English words correctly. During the workshop, students showed a great enthusiasm and all activities ran well. It is expected that form that point forward, students will be used to using Oxford dictionary and mispronunciation problems can be avoided.

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Proenca, Jorge, Carla Lopes, Michael Tjalve, Andreas Stolcke, Sara Candeias, and Fernando Perdigao. "Mispronunciation Detection in Children's Reading of Sentences." IEEE/ACM Transactions on Audio, Speech, and Language Processing 26, no. 7 (July 2018): 1207–19. http://dx.doi.org/10.1109/taslp.2018.2820429.

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Ge, Zhenhao, Sudhendu R. Sharma, and Mark J. T. Smith. "Improving mispronunciation detection using adaptive frequency scale." Computers & Electrical Engineering 39, no. 5 (July 2013): 1464–72. http://dx.doi.org/10.1016/j.compeleceng.2012.12.001.

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Ceylan, Mustafa, and Berrin Baydık. "Examination of reading skills of students who are poor readers in different text genres." Cypriot Journal of Educational Sciences 13, no. 2 (June 26, 2018): 178–91. http://dx.doi.org/10.18844/cjes.v13i2.3119.

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The purpose of this study was to compare the reading skills of fourth graders who were poor readers in different text genres (story and informative text). Fiftysix fourth grade students who were poor readers participated in this study. Reading rates, reading accuracies, reading errors and reading prosody characteristics of the students were examined in the study. The results of the study showed that reading rates of the students were higher in informative text. In addition, reading accuracies of the students were not differentiated according to text genre. The students made more errors of mispronunciation, word insertion, and repetition of word part, self correction, letter insertion-omission, syllable insertion-omission, letter reversing and conversion of the word final in informative text. The big proportions of mispronunciations of the students were reading the word as a visually similar word in both the story (78%) and the informative text (79%). While the students obtained higher expression and volume scores in the informative text, they read the story with a more suitable pace. Keywords: Reading Disability, Reading Fluency, Story, Informational Text

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Akhtar, Shamila, Fawad Hussain, Fawad Riasat Raja, Muhammad Ehatisham-ul-haq, Naveed Khan Baloch, Farruh Ishmanov, and Yousaf Bin Zikria. "Improving Mispronunciation Detection of Arabic Words for Non-Native Learners Using Deep Convolutional Neural Network Features." Electronics 9, no. 6 (June 9, 2020): 963. http://dx.doi.org/10.3390/electronics9060963.

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Computer-Aided Language Learning (CALL) is growing nowadays because learning new languages is essential for communication with people of different linguistic backgrounds. Mispronunciation detection is an integral part of CALL, which is used for automatic pointing of errors for the non-native speaker. In this paper, we investigated the mispronunciation detection of Arabic words using deep Convolution Neural Network (CNN). For automated pronunciation error detection, we proposed CNN features-based model and extracted features from different layers of Alex Net (layers 6, 7, and 8) to train three machine learning classifiers; K-nearest neighbor (KNN), Support Vector Machine (SVM) and Random Forest (RF). We also used a transfer learning-based model in which feature extraction and classification are performed automatically. To evaluate the performance of the proposed method, a comprehensive evaluation is provided on these methods with a traditional machine learning-based method using Mel Frequency Cepstral Coefficients (MFCC) features. We used the same three classifiers KNN, SVM, and RF in the baseline method for mispronunciation detection. Experimental results show that with handcrafted features, transfer learning-based method and classification based on deep features extracted from Alex Net achieved an average accuracy of 73.67, 85 and 93.20 on Arabic words, respectively. Moreover, these results reveal that the proposed method with feature selection achieved the best average accuracy of 93.20% than all other methods.

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Allen, Irving Lewis. "Sly Slurs: Mispronunciation and Decapitalization of Group Names." Names 36, no. 3-4 (December 1988): 217–24. http://dx.doi.org/10.1179/nam.1988.36.3-4.217.

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Tamási, Katalin, Cristina McKean, Adamantios Gafos, Tom Fritzsche, and Barbara Höhle. "Pupillometry registers toddlers’ sensitivity to degrees of mispronunciation." Journal of Experimental Child Psychology 153 (January 2017): 140–48. http://dx.doi.org/10.1016/j.jecp.2016.07.014.

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Ambalegin, Ambalegin, and Tomi Arianto. "English Vowels and Consonants Mispronunciation of the Seventh President of Republic of Indonesia in His Official English Speeches and Its Influencing Factors." LANGUAGE LITERACY: Journal of Linguistics, Literature, and Language Teaching 2, no. 2 (December 17, 2018): 113. http://dx.doi.org/10.30743/ll.v2i2.678.

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This research aimed to find out the mispronunciation of English vowels and consonants of the seventh president of Republic of Indonesia, Mr. Joko Widodo in his official English speeches based on the standard of British English Received Pronunciation (RP) and the factors influencing his English vowels and consonants mispronunciation. This research is a descriptive qualitative research. In collecting data, the researchers used observation method with non-participatory technique (Sudaryanto, 2015). In analyzing the data, the researchers used articulatory identity method (Sudaryanto, 2015). It was found that the consonant sounds /θ/, /ð/, /v/, /z/, /ʃ/ were pronounced incorrectly, the vowel sounds/ə/, /ɒ/, /ɛ/, /i/, /e/, /ɪ/ were pronounced inconsistently, and the diphthong sounds /ɪə/, /eɪ/, /əʊ/ and /aʊ/ were pronounced incorrectly. The consonant sound /l/ in the middle of the word was not pronounced. The consonant sound /j/ in the middle of the word is omitted. The consonant sounds /g/, /tʃ/, and /r/ were pronounced the same as the spelling. The consonant sounds /t/, /s/, /k/ at the end of the words were omitted. The letter y sounded /ɪ/ at the end of the word was pronounced as /e/. The diphthong sounds /ɪə/, /eɪ/, /əʊ/ and /aʊ/ were pronounced as /ɪ/, /ʌ/, /ɛ/, /ə/, /e/, and /ͻ/. The factors influencing the mispronunciation of English vowel and consonant sounds were mother tongue interference, sound system differences between Indonesian and English, the influence of spelling on pronunciation, educational background, and environmental background.

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Stefani, Ranni Putri, and Ahmad Roba’i. "An Analysis on the Tendency of Pronunciation Made by Students with Indonesian Linguistic Background." TEKNOSASTIK 16, no. 1 (April 6, 2019): 15. http://dx.doi.org/10.33365/ts.v16i1.129.

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The compulsory of speaking English to communicate at campus environment made the writers interested in the tendency of English pronunciation made by English students with Indonesian linguistic background. The question appeared was what kinds of difficulties that the learners face when they pronounce English words or when they speak in English. The objective was to find out the tendency of the mistakes they make. The data were collected by conducting direct observation in and outside classes. The talks or presentations made by the students were recorded. From the observation, the writers listed mispronounced words. The writers then used the words in written sentences and asked students to read those sentences. The students were also interviewed in order to have another measurement to determine the tendency occurring in the data. As results, most of the mispronunciation problems found were related to vowels, consonants and word stress. These are the most noticeable findings among other issues discovered after conducting the research.Key Words: English, foreign language, mispronunciation, phonetics, phonology

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Yamakawa, Kimiko, Shigeaki Amano, and Mariko Kondo. "Vietnamese speakers' mispronunciation of Japanese singleton and geminate stops." Acoustical Science and Technology 43, no. 5 (September 1, 2022): 241–50. http://dx.doi.org/10.1250/ast.43.241.

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Farooq, Mahwish, and Asim Mahmood. "The Acoustic Effect of Urdu Phonological Rules on English Speech." Linguistics and Literature Review 7, no. 1 (March 26, 2021): 83–98. http://dx.doi.org/10.32350/llr.71.07.

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The paper is about the acoustic effect of Urdu phonological rules on Pakistani Urdu speakers' English speech. The objective of the study is to discuss the phenomenon of multiple pronunciations of an English word that has the same spellings, meaning, and part of speech but different pronunciations in the English speech of Urdu speakers. Sometimes these alternative pronunciations are considered mispronunciation rather than multiple pronunciations. The primary purpose of this study is to make a boundary-line between mispronunciations and multiple pronunciations of English vocabulary. Thus, an acoustic analysis of Urdu speakers' English speech has been done by collecting speech data of 30 Urdu speakers from the Public sector universities of Pakistan. Consequently, this paper caters to language-dependent variations of Urdu. This paper only deals with three phonological rules, i.e., segment alternation, ellipsis, epenthesis, which become the cause for re-syllabification of English words. These three foci of research have been selected because the data analysis has confirmed that the 'multiple pronunciation' is mainly occurred due to these three elements. These three categories cover several sub-categories that cover many instances in the data analysis. The data also confirms that phonological variations occur due to stress shifting in Urdu speakers' English speech in Pakistan.

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Tabula, Rommel Valencia, Sawitri Suwanaroa, and Sutarat Polerk. "An Investigation of Factors Causing English Mispronunciation of Students in English for International Communication." International Journal of Linguistics, Literature and Translation 3, no. 11 (November 30, 2020): 194–205. http://dx.doi.org/10.32996/ijllt.2020.3.11.19.

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English has been recognized as a lingua franca in different aspects of communication such as international business, academic context, science and technology. Despite the constant efforts of developing English education in Thailand, studies have shown that the achievement of Thai students was still unsatisfactory. Additionally, previous studies revealed Thai EFL learners faced a number of difficulties in pronunciation and speaking. The purposes of this study were to investigate the levels of the factors and the most and least factors causing in English mispronunciation of 2nd and 3rd year students in EIC at RMUTL Tak campus. Fifty-one students were purposively selected from EIC of 2nd and 3rd year in 2019. The research instrument included questionnaire and adopted Likert scale for data analysis. The results found that 2nd and 3rd year students in English for International Communication (EIC) Program evaluated the factor causing in English mispronunciation found that 1) the first language interference factor have the highest mean value 2) phonetic ability factor 3) experience in studying English factor and 4) motivation factor have the lowest mean value.

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Algethami, Ghazi. "Phonemic Characterization of the Production of English Consonants by Nonnative Saudi Speakers." International Journal of Language and Literary Studies 4, no. 4 (December 29, 2022): 111–21. http://dx.doi.org/10.36892/ijlls.v4i4.1145.

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The current study characterizes the production of English consonants by Saudi L2 speakers and offers pedagogical implications for teachers and curriculum designers. Fifteen nonnative Saudi speakers, with at least one of year of residence in an English-speaking country, were recorded individually reading an English passage containing all the English consonants. Their recordings were subjected to a segmental, phonemic analysis to identify and describe any phonemic mispronunciation. The following consonants were found challenging to the Saudi L2 speakers: /v/, /?/, /p/ and /?/. Their production of these consonants was characterized by devoicing of /v/, inserting /g/ after /?/, voicing or lack of aspiration of /p/, and trilling or tapping of /?/. L1 influence played the main role in their mispronunciation. Their production of /v/ and /p/ resulted in phonemic substitutions with /f/ and /b/, respectively. These substitutions have the potential of being detrimental to speech intelligibility according to the Functional Load Principle and Lingua Franca Core; therefore, they should be prioritized in teaching English pronunciation to Saudi learners. The paper concludes by outlining pedagogical implications and offering tips for teaching English pronunciation to Saudi learners.

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McNeill, Brigid C., and Anne Hesketh. "Developmental complexity of the stimuli included in mispronunciation detection tasks." International Journal of Language & Communication Disorders 45, no. 1 (January 2010): 72–82. http://dx.doi.org/10.3109/13682820902745479.

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Agustine, Dianatalia, Indah Arvianti, and Eko Heriyanto. "THE IMPROVEMENT OF MISPRONUNCIATION ENCOUNTERED BY MOST YOUNG ENGLISH LEARNERS." Jurnal CULTURE (Culture, Language, and Literature Review) 9, no. 1 (May 11, 2022): 94–118. http://dx.doi.org/10.53873/culture.v9i1.243.

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Mispronunciation is a critical issue encountered by most young English learners in a second language learning that causes low spoken English proficiency, which plays important roles today. The objectives of this study were to identify the segmental changes resulted in the articulation of English mispronounced words produced by most young learners, to describe the different elements between Indonesian and English sound systems, and to explain the phonological interference of mother tongue in English mispronunciation. This study uses descriptive qualitative research design performed on ten primary school students selected by using purposive sampling in Semarang. Data were collected by using simak method and analyzed by using padan fonetik artikulatoris method. The data suggest that the majority of the participants had difficulty in articulating the words with absent phonemic segments /ɪ, æ, əː, ɔ, ʌ, eɪ, ʊə, ɪə, aɪə, ʃ, θ, ð, ʒ, voiced v/, silent letters <b, d, e, t, w, gh, and r in some cases>, spelling patterns <th, ow, ph, ie, ueue, ough>, and tricky words including several English borrowings that have inconsistent spelling pronunciation. The results showed that the interference of L1 sounds and pronunciation rules occurred through substitution of closest native sounds for absent phonemes, insertion of native sounds, and negative transfer of L1 spelling pronunciation. It can be concluded that most of the young learners mispronounced on words with absent phonemic segments, silent letters, spelling patterns of many letters combination, and several English borrowings.

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Park, Jung-eun. "A Study on Mispronunciation of Korean Consonants by Mongolian Learners." Urimalgeul: The Korean Language and Literature 65, no. ll (June 2015): 127–54. http://dx.doi.org/10.18628/urimal.65..201506.127.

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Huang, Hao, Haihua Xu, Xianhui Wang, and Wushour Silamu. "Maximum F1-Score Discriminative Training Criterion for Automatic Mispronunciation Detection." IEEE/ACM Transactions on Audio, Speech, and Language Processing 23, no. 4 (April 2015): 787–97. http://dx.doi.org/10.1109/taslp.2015.2409733.

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Saputri, Tiyas, Mujad Didien Afandi, and Anharu Minasalim Mushaf. "The Students’ Responses of Video Recording and E-Sorogan Learning Methods to Improve Pronunciation." Bidayatuna Jurnal Pendidikan Guru Mandrasah Ibtidaiyah 5, no. 1 (March 17, 2022): 81. http://dx.doi.org/10.54471/bidayatuna.v5i1.1578.

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Mispronunciation leads to misunderstanding because the inaccuracy in pronouncing words may distort the interpretation of ideas in communication. However, using video recording and e-Sorogan learning methods can be the solution to improve students’ pronunciation, especially the ASD and ADHD student. This study purposes to find out the students' responses to the use of these methods to the 39 elementary students, including a student with ASD and ADHD. This study used descriptive qualitative. The collected data were from the questionnaire survey. Next, the data collected from the questionnaire survey was analyzed descriptive qualitatively through the data in the table and based on empirical data. The results indicated that the students' responses to these methods were positive. It can be proved with the data presented in the table. To conclude, the students agree and even strongly agree with the use of these methods to improve their pronunciation although only a few of them disagree with that. Most of them like these methods because they were appropriate, effective, interesting, useful, and successful to improve their pronunciation. Even, they are able to do self-evaluation and correct the mispronunciation from the video made.

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Uddin, Mohammad. "Pedagogical implication of Audio-Articulation Method to defossilize /e/এ/ sound in English pronunciation of Bangladeshi EFL learners." International Journal of Linguistics and Translation Studies 2, no. 4 (October 31, 2021): 47–61. http://dx.doi.org/10.36892/ijlts.v2i4.166.

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The purpose of this article is to show how to defossilize the English /e/ sound which is pronounced by the Bengali learners of English instead of /ei/ sound in such words like ape, make and day etc. This mispronunciation creates confusion among the native speakers of English and the Bengali learners’ pronunciation loses comprehensibility to the listeners. The author, in his experience, observes that Phonological fossilization of /e/ sound in the Bengali speakers of English is the main cause of this mispronunciation and incomprehensibility level in them. The present study is a detail lesson plan to defossilize the problem causing /e/ sound by using Audio Articulation Method propounded by Mehmet Demirezen in the classroom practice. As a fossilized pronunciation error correction method, the audio articulation method can play a vital role in creating awareness of a fossilized sound among the EFL learners in Bangladesh. By applying different kinds of drills, such as, conversation drills, substitution drills, question-answer drills, repetition drills, language games etc in the class hour, the teachers can endeavor to defossilize the problem causing sounds among the students and both the teachers and learners in Bangladesh can be benefited through this practice.

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SAITO, KAZUYA. "Communicative focus on second language phonetic form: Teaching Japanese learners to perceive and produce English /ɹ/ without explicit instruction." Applied Psycholinguistics 36, no. 2 (April 29, 2013): 377–409. http://dx.doi.org/10.1017/s0142716413000271.

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ABSTRACTThe current study examines in depth how two types of form-focused instruction (FFI), which are FFI with and without corrective feedback (CF), can facilitate second language speech perception and production of /ɹ/ by 49 Japanese learners in English as a Foreign Langage settings. FFI effectiveness was assessed via three outcome measures (perception, controlled production, and spontaneous production) and also according to two lexical contexts (trained and untrained items). Two experimental groups received 4 hr of FFI treatment to notice and practice the target feature of /ɹ/ (but without any explicit instruction) in meaningful discourse. A control group (n = 14) received comparable instruction in the absence of FFI. During FFI, the instructors provided CF only to students in the FFI + CF group (n = 18) by recasting their mispronunciations of /ɹ/, while no CF was provided to those in the FFI-only group (n = 17). Analyses of pre- and posttests showed that FFI itself can sufficiently promote the development of speech perception and production of /ɹ/ and the acquisitional value of CF in second language speech learning remains unclear. The results suggest that the beginner learners without much phonetic knowledge on how to repair their mispronunciation of /ɹ/ should be encouraged to learn the target sound only through FFI in a receptive mode without much pressure for modified output.

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Cao, Haiyang, and Chengmei Dong. "An English Pronunciation Error Detection System Based on Improved Random Forest." Mobile Information Systems 2022 (April 19, 2022): 1–10. http://dx.doi.org/10.1155/2022/6457286.

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The existing English pronunciation error detection methods are more oriented to the detection of wrong pronunciation, and lack of targeted improvement suggestions for pronunciation errors. With the aim of solving this problem, the paper proposes an English pronunciation error detection system based on improved random forest. Firstly, a speech corpus is constructed along with the evaluation of the acoustic features. Then an improved random forest detection algorithm is designed. The algorithm inputs rare mispronunciation data into a GAN neural network to generate new class samples and improve the uneven distribution of mispronunciation data in the sample set. The distribution rules of the pronunciation data are extracted layer by layer by stacking deep SDAEs, and the coefficient penalties and reconstruction errors of each coding layer are combined to identify the features associated with the wrong pronunciation in the high-dimensional data. Furthermore, a forest decision tree is constructed using the reduced-dimensional feature-based data to improve the pronunciation detection accuracy. Finally, the extracted 39 Mel Frequency Cepstral Coefficient (MFCC) acoustic features are used as the input of the improved random forest classifier to construct a classification error detection model. The experimental results indicate that the designed system achieves a high accuracy of English pronunciation detection.

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Franco, Horacio, Harry Bratt, Romain Rossier, Venkata Rao Gadde, Elizabeth Shriberg, Victor Abrash, and Kristin Precoda. "EduSpeak®: A speech recognition and pronunciation scoring toolkit for computer-aided language learning applications." Language Testing 27, no. 3 (July 2010): 401–18. http://dx.doi.org/10.1177/0265532210364408.

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SRI International’s EduSpeak® system is a software development toolkit that enables developers of interactive language education software to use state-of-the-art speech recognition and pronunciation scoring technology. Automatic pronunciation scoring allows the computer to provide feedback on the overall quality of pronunciation and to point to specific production problems. We review our approach to pronunciation scoring, where our aim is to estimate the grade that a human expert would assign to the pronunciation quality of a paragraph or a phrase. Using databases of nonnative speech and corresponding human ratings at the sentence level, we evaluate different machine scores that can be used as predictor variables to estimate pronunciation quality. For more specific feedback on pronunciation, the EduSpeak toolkit supports a phone-level mispronunciation detection functionality that automatically flags specific phone segments that have been mispronounced. Phone-level information makes it possible to provide the student with feedback about specific pronunciation mistakes.Two approaches to mispronunciation detection were evaluated in a phonetically transcribed database of 130,000 phones uttered in continuous speech sentences by 206 nonnative speakers. Results show that classification error of the best system, for the phones that can be reliably transcribed, is only slightly higher than the average pairwise disagreement between the human transcribers.

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Apriyanti, Difiani, and Anggara Payudha. "Some Words Mispronunciation in Pro News Today at Pro News Radio." Journal Polingua : Scientific Journal of Linguistics, Literature and Education 3, no. 1 (March 28, 2018): 1–8. http://dx.doi.org/10.30630/polingua.v3i1.6.

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Learning English through media-printed media such as newspaper printed in English and electronic media such as Radio andTelevision present in English. In Padang, West Sumatra, Pro News Radio is one of the stations which broadcast an English program. It isnamed Pro News Today. Most of the listeners are people in West Sumatra who want to learn English. Because many people are hopingmuch from this program, it is a must to see whether the program is being presented perfectly. Referring to this reason, the writersconducted a project about mispronunciation words that occur by the newsreaders during broadcasting the news. By applying dictionaryreference.com the writers find out that they did mispronounce several words during broadcasting, and there were same words which aremispronounced by the two different newsreaders. The writers also did interview to the newsreaders whether they are aware of theirmistake or not. From their answer, it can be concluded that they do not realize that they have made the mistake. The writers hope that ProNews Radio gives more attention to the English skill of the newsreaders in English program.

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Wu, Chao, and Pan Wang. "Exploring Visual Mispronunciation at Segmental Level among EL 2 Chinese Students." English Language Teaching 13, no. 10 (September 24, 2020): 120. http://dx.doi.org/10.5539/elt.v13n10p120.

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In our pronunciation courses, segmental level in English pronunciation plays a very important role in perception and teaching of English pronunciation. This research aims to investigate into the most salient pronunciation problems at segmental level by fresh college students from Mainland China through an experimental study, and it is found that the mismatches identified in the segmental level of English pronunciation are corresponded with the phonological features of the utterance of Chinese English. Moreover, in order to improve fresh college students’ pronunciation and achieve the pronunciation of Standard English, some pedagogical implications and suggestions about teaching strategies are provided in this study which aimed at the most salient mismatches discovered in the research findings. 

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Huang, Guimin, Qiupu Chen, and Hongtao Zhu. "A Mispronunciation Detection Method of Confusing Vowel Pair for Chinese Students." Journal of Physics: Conference Series 1693 (December 2020): 012102. http://dx.doi.org/10.1088/1742-6596/1693/1/012102.

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Koniaris, Christos, Giampiero Salvi, and Olov Engwall. "On mispronunciation analysis of individual foreign speakers using auditory periphery models." Speech Communication 55, no. 5 (June 2013): 691–706. http://dx.doi.org/10.1016/j.specom.2013.01.004.

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Redondo Reyes, Pedro. "Language, vocal organs and barbarophonoi." Humanitas, no. 78 (December 15, 2021): 33–50. http://dx.doi.org/10.14195/2183-1718_78_2.

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Strabo (14.2.28), commenting on the Homeric term barbarophonoi, upholds the onomatopoeic origin of barbaros and outlines an history of its usage, which goes from the meaning of “speak roughly” to the one of “mispronunciation” of Greek. In order to interpret the passage, pertinent texts from the medical and acoustic-musical are commented; concluding thus, that Strabo knows the reflections on the voice and language that lead him to a definition of barbaros based, mainly, on a linguistic criterion.

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AlTalmas, Tareq, Salmiah Ahmad, Nik Nur Wahidah Nik Hashim, Surul Shahbudin Hassan, and Wahju Sediono. "Characteristics with opposite of quranic letters mispronunciation detection: a classifier-based approach." Bulletin of Electrical Engineering and Informatics 11, no. 5 (October 1, 2022): 2817–27. http://dx.doi.org/10.11591/eei.v11i5.3715.

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Reading Quran for non-Arab is a challenge due to different mother tongues. learning Quran face-to-face is considered time-consuming. The correct pronunciation of Makhraj and Sifaat are the two things that are considered difficult. In this paper, Sifaat evaluation system was developed, focusing on Sifaat with opposites for teaching the pronunciation of the Quranic letters. A classifier-based approach has been designed for evaluating the Sifaat with opposites, using machine learning technique; the k-nearest neighbour (KNN), the ensemble random undersampling (RUSBoosted), and the support vector machine (SVM). Five separated classifiers were designed to classify the Quranic letters according to group of Sifaat with opposites, where letters that are classified to the wrong groups are considered mispronounced. The paper started with identifying the acoustic features to represent each group of Sifaat. Then, the classification method was identified to be used with each group of Sifaat, where best models were selected relying on various metrics; accuracy, recall, precision, and F-score. Cross-validation scheme was then used to protect against overfitting and estimate an unbiased generalization performance. Various acoustic features and classification models were investigated, however, only the outperformed models are reported in this paper. The results showed a good performance for the five classification models.

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An, Li-li, Yan-nian Wu, Zhi Liu, and Run-sheng Liu. "An Application of Mispronunciation Detecting Network for Computer Assisted Language Learning System." Journal of Electronics & Information Technology 34, no. 9 (July 9, 2013): 2085–90. http://dx.doi.org/10.3724/sp.j.1146.2012.00125.

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Maikanti, Sale, Jurgen Martin Burkhardt, Mei Fung Yong, Salina Binti Husain, and Olúwadọrọ̀ Jacob Oludare. "Mispronunciation of High Front and Low Hausa Vowels among the Yorùbá Speakers." Malaysian Journal of Social Sciences and Humanities (MJSSH) 6, no. 7 (July 10, 2021): 321–35. http://dx.doi.org/10.47405/mjssh.v6i7.921.

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Pronunciation in second language learning is sometimes challenging, especially the vowels. Vowels such as [i] and [a] are found both in Hausa and Yorùbá but [i:] and [a:] are peculiar to Hausa alone. While Hausa has short and long vowels, Yorùbá has only oral and nasal vowels in their vowel inventories. Such phonemic differences constitute learning challenges, especially for the Yorùbá native speakers. This is a cross-sectional study design using mixed methods to examines the production of high front vowels: [i], and [i:], as well as low: [a], and [a:] Hausa vowels by the Yorùbá speakers to identify which group perform better between group 1 (Yorùbá native speakers who learned Hausa in the secondary school before going to the college of education), and group 2 (Yorùbá native speakers who learned Hausa informally before going to the college of education). The study also seeks to find out vowel substitutions that occur in the pronunciation tasks using 80 participants from 18 years old and above from the College of Education system in Nigeria who were selected based on purposive sampling. The findings were discussed in line with Flege & Bohn’s (2020) ‘Revised Speech Learning Model’. 8 stimuli were audio-recorded, transcribed, and rated by two independent raters, in addition to participant observation techniques adapted. The results of the Mann-Whitney test revealed that group 2 performed better than group 1. The study discovered also that the short [a] in the first and second syllables had the highest frequency of substitution compared to [i], [i:] and [a:] vowels. Such problems have pedagogical implications for learning Hausa as a second language.

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Huang, Hao, Haihua Xu, Ying Hu, and Gang Zhou. "A transfer learning approach to goodness of pronunciation based automatic mispronunciation detection." Journal of the Acoustical Society of America 142, no. 5 (November 2017): 3165–77. http://dx.doi.org/10.1121/1.5011159.

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Krecichwost, Michal, Zuzanna Miodonska, Pawel Badura, Joanna Trzaskalik, and Natalia Mocko. "Multi-channel acoustic analysis of phoneme /s/ mispronunciation for lateral sigmatism detection." Biocybernetics and Biomedical Engineering 39, no. 1 (January 2019): 246–55. http://dx.doi.org/10.1016/j.bbe.2018.11.005.

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Rifka, Rifka Nusrath, and Abdul Halik.AF. "Investigating the vowel mispronunciation of undergraduate students of the Faculty of Management and Commerce, South Eastern University of Sri Lanka." Journal of Social Sciences and Management Studies 1, no. 3 (June 5, 2022): 35–41. http://dx.doi.org/10.56556/jssms.v1i3.157.

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This study was conducted to investigate the vowel mispronunciation of undergraduate students of the Faculty of Management and Commerce, South Eastern University of Sri Lanka. The aim of this study was to identify the problems and difficulties faced by the students in pronouncing vowel sounds in their loud reading and speaking, and the factors which affects students’ pronunciation development. It has been observed that learners encounter number of pronunciation problems and difficulties in speaking and loud reading. In this study, fifty 2nd year Students of the Faculty of Management and Commerce, South Eastern University of Sri Lanka were randomly selected as sample population for investigation. The primary data were collected using qualitative and quantitative methods, and the research instruments used in this study were oral pronunciation test, questionnaire and audio tape recording. The instruments enabled the researcher to identify vowel mispronunciation with their opinions about pronunciation. According to the data analysis, the findings show that the learners encountered difficulties in pronouncing vowel sounds such as /iː/ as /i/, /uː/ as /u/ and /əʊ/ as /ɔ/. Moreover, the opinion survey revealed that the learners show lack of interest in learning pronunciation and many factors that affect their pronunciation development. These pronunciation problems and difficulties can be overcome and improved through implementing pronunciation as a separate component like grammar and writing in English as a Second Language curriculum of Department of English Language Teaching of South Eastern University of Sri Lanka.

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Stefanov, Simeon. "ВЛАДКО МУРДАРОВ. РАЗНИ СЪВЕТИ ЗА ГЛАГОЛИТЕ / VLADKO MURDAROV. MISCELANEOUS TIPS ABOUT VERBS." Journal of Bulgarian Language 68, no. 68.04 (December 30, 2021): 165–67. http://dx.doi.org/10.47810/bl.68.21.04.15.

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The review is dedicated to the new book of Prof. Vladko Murdarov, DSc „Miscelaneous tips about verbs“, which draws attention to the hesitations and mistakes that Bulgarians most often make with verbs in their oral speech. Examples related to the mispronunciation of verbs and verb forms, as well as the expressions in which they are included, are selected, and the possible reasons for the mistakes are indicated. An assessment of a number of new phenomena in our language, manifested in public speech, which are waiting for the most correct decision, is also given.

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Đào, Mục-Đích, and Anh-Thư Nguyễn. "Vietnamese Tones Produced by Australian Vietnamese Speakers." Heritage Language Journal 14, no. 3 (December 31, 2017): 224–47. http://dx.doi.org/10.46538/hlj.14.3.1.

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This paper reports an acoustic study that examined the tonal features of Vietnamese language used by the Vietnamese community in Australia. The target of this examination is the comparative analysis of the phonetic characteristics of tones produced by Vietnamese in Australia and in Vietnam. Tones produced by young (n=10) and older (n=10) Vietnamese Australians residing in Brisbane, Australia, were acoustically examined and compared with those produced by corresponding young (n=10) and older (n=10) Vietnamese residing in either Ho Chi Minh City or Can Tho City, Vietnam. The results showed that the main patterns of mispronunciation of tones by the young Vietnamese in Australia (YVA) include (i) confusing tones that are in the same registers or/and have similar characteristics, (ii) the tendency to pronounce complicated tones as simple tones, and (iii) confusing the diacritics marking tones. By “mispronunciation”, we mean the differences in tones used in Brisbane, Australia from the tones used in Vietnam. This study also examined the frequency of the contour of all tones produced by all four groups. The results show significant differences in terms of the frequency and distribution of irregular and common tone contours between the YVA group and the three other groups, suggesting that the YVA group failed to produce the tones correctly or did not reach the required standard of tone production of contemporary Southern Vietnamese. In addition, the findings with respect to tone contours showed that the tonal range of the YVA group is narrower than that of the other three groups.

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Wang, Shunlan. "Exploring the Teaching Mode of English Audiovisual Speaking in Multimedia Network Environment." Advances in Multimedia 2022 (July 15, 2022): 1–9. http://dx.doi.org/10.1155/2022/2424380.

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Introducing multimedia network tools in English audiovisual teaching and building a new model of network-based multimedia teaching can make English audiovisual teaching more in line with students’ cognitive thinking characteristics and processes. This can improve the overall efficiency of English teaching in schools. Computers have been widely used in language evaluation and speech recognition for language learning, and speech recognition technology is an important reflection of the level of language learning. The large amount of language signal data, complex pronunciation changes, and high dimensionality of pronunciation feature parameters in the language learning process make it difficult to identify pronunciation features. The computational volume of pronunciation evaluation and recognition is too large, which requires high hardware resources and software resources to realize high-speed processing of massive pronunciation signals. To address the problem of low recognition rate of English pronunciation, this study proposes a sound recognition algorithm based on adaptive particle swarm optimization (PSO) matching pursuit (MP) sparse decomposition. The algorithm firstly improves the parameter adaptive setting of PSO based on the particle and population evolution rate, establishes parameter adaptive PSO, and realizes the optimization of adaptive PSO optimized MP sparse decomposition. The continuous Gabor super-complete atomic set is constructed based on the continuous space search property of PSO to improve the optimal atomic matching of the evolutionary process. Finally, the recognition of English pronunciation is realized by the support vector machine (SVM) algorithm. The test results show that the misjudgement rate for different mispronunciations is less than 1% when the system is used to evaluate the English pronunciation level. It proves that the method can effectively detect the mispronunciation and has high evaluation accuracy.

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Alqunayeer, Huda. "Pronunciation Errors of Letter “G” in English Language Made by Saudi Undergraduate Students." English Language and Literature Studies 6, no. 4 (November 30, 2016): 104. http://dx.doi.org/10.5539/ells.v6n4p104.

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The primary goal of the present study is to identify the problematic areas in the pronunciation of the letter “g” in English written words made by Saudi female learners of English as a foreign language, and the reasons for the weakness associated with mispronunciation of English written words which contain this letter. The population of the study was the female students (90 students) and their English language teachers (12 teachers) at the Qassim University during the academic year (2014-2015). There were two types of instruments used in this study. The first was a pronunciation test for the student participants in order to investigate the problematic areas of pronouncing “g” in different environments in different words; and the second a questionnaire for the teacher participants to provide comprehensive data about the causes of these errors of pronouncing “g” committed by EFL female students at Qassim University. Ninety female students were included for the pronunciation test and 12 teachers were asked to answer the questionnaire. Simple percentage was used for analyzing the data of recording words (pronunciation test). Results of the students’ recording words revealed that the participants mispronounced “g” before nasals (68%). According to the results of the teachers’ responses to the questionnaire suggested many factors that can cause difficulties for students in terms of pronouncing “g” in English written words. According to them, these difficulties are concerned with reading difficulties, nonstandard spellings, letters that follow “g” (many of them may become combinations), loan words, orthography (no correspondence between the English alphabets and their sounds). The researcher offers recommendations that might help teachers and students to overcome and reduce these mispronunciations of this letter in English written words.

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Journal articles on the topic 'Mispronunciation'

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