Academic literature on the topic 'Language identification'

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Journal articles on the topic "Language identification"

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Suganthi, Mrs Dr V., C. Thavapriya, and T. Mirudhu Bashini. "Sign Language Identification." International Journal of Research Publication and Reviews 5, no. 3 (2024): 5997–6001. http://dx.doi.org/10.55248/gengpi.5.0324.0855.

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Kumar, P. Vijay, and A. Raviteja A. Raviteja. "Automatic Indian Language Identification." International Journal of Scientific Research 2, no. 4 (2012): 79–82. http://dx.doi.org/10.15373/22778179/apr2013/31.

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MALMASI, SHERVIN, and MARK DRAS. "Multilingual native language identification." Natural Language Engineering 23, no. 2 (2015): 163–215. http://dx.doi.org/10.1017/s1351324915000406.

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AbstractWe present the first comprehensive study of Native Language Identification (NLI) applied to text written in languages other than English, using data from six languages. NLI is the task of predicting an author’s first language using only their writings in a second language, with applications in Second Language Acquisition and forensic linguistics. Most research to date has focused on English but there is a need to apply NLI to other languages, not only to gauge its applicability but also to aid in teaching research for other emerging languages. With this goal, we identify six typologica
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Alam, Salman. "Comparison of Various Models in the Context of Language Identification (Indo Aryan Languages)." International Journal of Science and Research (IJSR) 10, no. 3 (2021): 185–88. https://doi.org/10.21275/sr21303115028.

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PRATHIBA, GEETHA, VELPULA SHRAVYA PATEL, PATHAK SHIVANI, and UPPUTALLA DIVYA. "LANGUAGE IDENTIFICATION FOR MULTILINGUAL MACHINE." Journal of Engineering Sciences 15, no. 10 (2024): 202–12. http://dx.doi.org/10.36893/jes.2024.v15i10.025.

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Language Identification for Multilingual Machine Translation is a crucial component in modern natural language processing systems, enabling accurate and efficient translation across multiple languages. This paper presents a comprehensive approach to language identification that enhances the performance of multilingual machine translation systems.The proposed method utilizes advanced machine learning techniques to automatically detect the language of a given text with high accuracy. By incorporating a variety of linguistic features and leveraging large-scale multilingual datasets, the system ca
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Koena, Mabokela. "INTEGRATION OF PHONOTACTIC FEATURES FOR LANGUAGE IDENTIFICATION ON CODE-SWITCHED SPEECH." International Journal on Natural Language Computing (IJNLC) 11, no. 1 (2022): 14. https://doi.org/10.5281/zenodo.6375524.

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In this paper, phoneme sequences are used as language information to perform code-switched language identification (LID). With the one-pass recognition system, the spoken sounds are converted into phonetically arranged sequences of sounds. The acoustic models are robust enough to handle multiple languages when emulating multiple hidden Markov models (HMMs). To determine the phoneme similarity among our target languages, we reported two methods of phoneme mapping. Statistical phoneme-based bigram language models (LM) are integrated into speech decoding to eliminate possible phone mismatches. Th
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Qafmolla, Nejla. "Automatic Language Identification." European Journal of Language and Literature 7, no. 1 (2017): 140. http://dx.doi.org/10.26417/ejls.v7i1.p140-150.

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Automatic Language Identification (LID) is the process of automatically identifying the language of spoken utterance or written material. LID has received much attention due to its application to major areas of research and long-aspired dreams in computational sciences, namely Machine Translation (MT), Speech Recognition (SR) and Data Mining (DM). A considerable increase in the amount of and access to data provided not only by experts but also by users all over the Internet has resulted into both the development of different approaches in the area of LID – so as to generate more efficient syst
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Zissman, Marc A., and Kay M. Berkling. "Automatic language identification." Speech Communication 35, no. 1-2 (2001): 115–24. http://dx.doi.org/10.1016/s0167-6393(00)00099-6.

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Van Segbroeck, Maarten, Ruchir Travadi, and Shrikanth S. Narayanan. "Rapid Language Identification." IEEE/ACM Transactions on Audio, Speech, and Language Processing 23, no. 7 (2015): 1118–29. http://dx.doi.org/10.1109/taslp.2015.2419978.

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Ranasinghe, Tharindu, and Marcos Zampieri. "Multilingual Offensive Language Identification for Low-resource Languages." ACM Transactions on Asian and Low-Resource Language Information Processing 21, no. 1 (2022): 1–13. http://dx.doi.org/10.1145/3457610.

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Offensive content is pervasive in social media and a reason for concern to companies and government organizations. Several studies have been recently published investigating methods to detect the various forms of such content (e.g., hate speech, cyberbullying, and cyberaggression). The clear majority of these studies deal with English partially because most annotated datasets available contain English data. In this article, we take advantage of available English datasets by applying cross-lingual contextual word embeddings and transfer learning to make predictions in low-resource languages. We
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Dissertations / Theses on the topic "Language identification"

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Botha, Gerrti Reinier. "Text-based language identification for the South African languages." Pretoria : [s.n.], 2007. http://upetd.up.ac.za/thesis/available/etd-090942008-133715/.

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Yin, Bo Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Language identification with language and feature dependency." Awarded By:University of New South Wales. Electrical Engineering & Telecommunications, 2009. http://handle.unsw.edu.au/1959.4/44045.

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The purpose of Language Identification (LID) is to identify a specific language from a spoken utterance, automatically. Language-specific characteristics are always associated with different languages. Most existing LID approaches utilise a statistical modelling process with common acoustic/phonotactic features to model specific languages while avoiding any language-specific knowledge. Great successes have been achieved in this area over past decades. However, there is still a huge gap between these languageindependent methods and the actual language-specific patterns. It is extremely useful t
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Newman, Jacob Laurence. "Language identification using visual features." Thesis, University of East Anglia, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.539371.

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Berkling, Kay Margarethe. "Automatic language identification with sequences of language-independent phoneme clusters /." Full text open access at:, 1996. http://content.ohsu.edu/u?/etd,204.

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Conti, Matteo. "Machine Learning Based Programming Language Identification." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20875/.

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L'avvento dell'era digitale ha contribuito allo sviluppo di nuovi settori tecnologici, i quali, per diretta conseguenza, hanno portato alla richiesta di nuove figure professionali capaci di assumere un ruolo chiave nel processo d'innovazione tecnologica. L'aumento di questa richiesta ha interessato particolarmente il settore dello sviluppo del software, a seguito della nascita di nuovi linguaggi di programmazione e nuovi campi a cui applicarli. La componente principale di cui è composto un software, infatti, è il codice sorgente, il quale può essere rappresentato come un archivio di uno o più
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Munday, Emma Rachel. "Language and identification in contemporary Kazakhstan." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/6200.

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In the years since the dissolution of the Soviet Union Central Asia has experienced wide-reaching and ongoing social change. The structures and values of all social strata have been questioned and re-evaluated in a continuing exploration of what it means to be part of the post-Soviet space. Within this space, identity formation and reformation has been a pre-eminent process for individuals, for groups of all kinds and for the newly emerging states and their leaders. Through the analysis of individual interviews and selected newspaper extracts and government policy documents this study explores
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Nkadimeng, Calvin. "Language identification using Gaussian mixture models." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/4170.

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Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2010.<br>ENGLISH ABSTRACT: The importance of Language Identification for African languages is seeing a dramatic increase due to the development of telecommunication infrastructure and, as a result, an increase in volumes of data and speech traffic in public networks. By automatically processing the raw speech data the vital assistance given to people in distress can be speeded up, by referring their calls to a person knowledgeable in that language. To this effect a speech corpus was developed and various
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Avenberg, Anna. "Automatic language identification of short texts." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-421032.

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The world is growing more connected through the use of online communication, exposing software and humans to all the world's languages. While devices are able to understand and share the raw data between themselves and with humans, the information itself is not expressed in a monolithic format. This causes issues both in the human to computer interaction and human to human communication. Automatic language identification (LID) is a field within artificial intelligence and natural language processing that strives to solve a part of these issues by identifying languages from text, sign language
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Foran, Jeffrey (Jeffrey Matthew) 1977. "Missing argument referent identification in natural language." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80532.

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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.<br>Includes bibliographical references (p. 54-55).<br>by Jeffrey Foran.<br>S.B.and M.Eng.
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Gambardella, Maria-Elena. "Cleartext detection and language identification in ciphers." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-446439.

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In historical cryptology, cleartext represents text written in a known language ina cipher (a hand-written manuscript aiming at hiding the content of a message).Cleartext can give us an historical interpretation and contextualisation of themanuscript and could help researchers in cryptanalysis, but to these days thereis still no research on how to automatically detect cleartext and identifying itslanguage. In this paper, we investigate to what extent we can automaticallydistinguish cleartext from ciphertext in transcribed historical ciphers and towhat extent we are able to identify its languag
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Books on the topic "Language identification"

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United States. Bureau of Justice Assistance and Ohio. Office of Criminal Justice Services (1993- ), eds. I speak--: Language identification guide. 2nd ed. U.S. Dept. of Justice, Office of Justice Programs, Bureau of Justice Assistance, 2006.

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Jauhiainen, Tommi, Marcos Zampieri, Timothy Baldwin, and Krister Lindén. Automatic Language Identification in Texts. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-45822-4.

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Rao, K. Sreenivasa, and Dipanjan Nandi. Language Identification Using Excitation Source Features. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17725-0.

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Rao, K. Sreenivasa, V. Ramu Reddy, and Sudhamay Maity. Language Identification Using Spectral and Prosodic Features. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17163-0.

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United States. Bureau of the Census, ed. Language identification flashcard: 21st decennial census--1990. U.S. Dept. of Commerce, Bureau of the Census, 1990.

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Law, James, ed. The Early Identification of Language Impairment in Children. Springer US, 1992. http://dx.doi.org/10.1007/978-1-4899-4445-0.

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1956-, Law James Christopher, ed. The Early identification of language impairment in children. Chapman & Hall, 1992.

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1925-, Adler Sol, ed. Early identification and intensive remediation of language retarded children. Thomas, 1986.

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Keith, Lenz B., ed. The Word identification strategy. 2nd ed. University of Kansas, 1985.

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Shprintzen, Robert J. Syndrome identification for speech-language pathologists: An illustrated pocket guide. Singular Thomson Learning, 2000.

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Book chapters on the topic "Language identification"

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Palakodety, Shriphani, Ashiqur R. KhudaBukhsh, and Guha Jayachandran. "Language Identification." In Low Resource Social Media Text Mining. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5625-5_4.

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Gleason, H. A. "The Identification of Morphemes." In Language. Macmillan Education UK, 1994. http://dx.doi.org/10.1007/978-1-349-13421-2_19.

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Hazen, Timothy J. "Topic Identification." In Spoken Language Understanding. John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119992691.ch12.

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de Jong-Lendle, Gea. "Speaker Identification." In Language as Evidence. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-84330-4_9.

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Fobbe, Eilika. "Authorship Identification." In Language as Evidence. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-84330-4_7.

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Battye, Alison. "Identification and partnership." In Gestalt Language Processing. Routledge, 2024. http://dx.doi.org/10.4324/9781032717029-2.

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Jauhiainen, Tommi, Marcos Zampieri, Timothy Baldwin, and Krister Lindén. "Introduction to Language Identification." In Automatic Language Identification in Texts. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-45822-4_1.

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Schmidt, Anna Marie. "Cross-language consonant identification." In Language Experience in Second Language Speech Learning. John Benjamins Publishing Company, 2007. http://dx.doi.org/10.1075/lllt.17.18sch.

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Malmasi, Shervin, Iria del Río, and Marcos Zampieri. "Portuguese Native Language Identification." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99722-3_12.

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Winnemöller, Ronald. "Drive-by Language Identification." In Computational Linguistics and Intelligent Text Processing. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12116-6_42.

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Conference papers on the topic "Language identification"

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Uchoi, Enjula, Utkarsh Solanki, Udit Bhandral, Sahil Patiyal, Sahil Dogra, and Hargun Singh Khera. "Machine Learning-based Automatic Language Identification forIndian Languages." In 2024 International Conference on IoT, Communication and Automation Technology (ICICAT). IEEE, 2024. https://doi.org/10.1109/icicat62666.2024.10923467.

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Goswami, Dhiman, Marcos Zampieri, Kai North, Shervin Malmasi, and Antonios Anastasopoulos. "Multilingual Native Language Identification with Large Language Models." In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop). Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.naacl-srw.19.

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Agarwal, Milind, Joshua Otten, and Antonios Anastasopoulos. "Script-Agnosticism and its Impact on Language Identification for Dravidian Languages." In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.naacl-long.377.

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Farrell, Kevin R., Richard J. Mammone, and Allen Gorin. "Algebraic learning for language acquisition." In Substance Identification Technologies, edited by James L. Flanagan, Richard J. Mammone, Albert E. Brandenstein, et al. SPIE, 1994. http://dx.doi.org/10.1117/12.172523.

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Mabokela, Ronny. "Phone Clustering Methods for Multilingual Language Identification." In 9th International Conference on Natural Language Processing (NLP 2020). AIRCC Publishing Corporation, 2020. http://dx.doi.org/10.5121/csit.2020.101421.

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This paper proposes phoneme clustering methods for multilingual language identification (LID) on a mixed-language corpus. A one-pass multilingual automated speech recognition (ASR) system converts spoken utterances into occurrences of phone sequences. Hidden Markov models were employed to train multilingual acoustic models that handle multiple languages within an utterance. Two phoneme clustering methods were explored to derive the most appropriate phoneme similarities between the target languages. Ultimately a supervised machine learning technique was employed to learn the language transition
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Kargaran, Amir, Ayyoob Imani, François Yvon, and Hinrich Schuetze. "GlotLID: Language Identification for Low-Resource Languages." In Findings of the Association for Computational Linguistics: EMNLP 2023. Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.findings-emnlp.410.

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Huang, Yichen, Hongyan Wang, Jeroen van de Weijer, and Zhengfei Zhu. "Native Language Identification." In ACAI 2019: 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence. ACM, 2019. http://dx.doi.org/10.1145/3377713.3377781.

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Remnev, N. V. "NATIVE LANGUAGE IDENTIFICATION FOR RUSSIAN USING ERRORS TYPES." In International Conference on Computational Linguistics and Intellectual Technologies "Dialogue". Russian State University for the Humanities, 2020. http://dx.doi.org/10.28995/2075-7182-2020-19-1123-1133.

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The task of recognizing the author’s native (Native Language Identification—NLI) language based on a texts, written in a language that is non-native to the author—is the task of automatically recognizing native language (L1). The NLI task was studied in detail for the English language, and two shared tasks were conducted in 2013 and 2017, where TOEFL English essays and essay samples were used as data. There is also a small number of works where the NLI problem was solved for other languages. The NLI problem was investigated for Russian by Ladygina (2017) and Remnev (2019). This paper discusses
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Maier, Wolfgang, and Carlos Gómez-Rodríguez. "Language variety identification in Spanish tweets." In Proceedings of the EMNLP'2014 Workshop on Language Technology for Closely Related Languages and Language Variants. Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/w14-4204.

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Chakraborty, Joyshree, Priyankoo Sarmah, and Samudra Vijaya. "Spoken Language Identification of Four Tibeto-Burman languages." In 2020 23rd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA). IEEE, 2020. http://dx.doi.org/10.1109/o-cocosda50338.2020.9295008.

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Reports on the topic "Language identification"

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Nowell, P., and D. A. Stevens. User Manual for Tactical Language Identification Software. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada354329.

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Foged, Mette, and Cynthia van der Werf. Access to Language Training and the Local Integration of Refugees. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0004897.

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This paper examines whether language classes raises refugees' language proficiency and improves their socio-economic integration. Our identification strategy leverages the opening, closing, and gradual expansion of local language training centers in Denmark, as well as the quasi-random assignment of the refugees to locations with varying proximity to a language training center. First, we show that refugees' distance from the assigned language training center is as good as random conditional on initial placement. Second, we show that a one-hour decrease in commuting time increases total hours o
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Mendes, Diogo, Bruno Travassos, Adilson Marques, and Hugo Sarmento. Talent Identification and Development in Male Futsal: A Systematic Review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.2.0005.

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Review question / Objective: Identify and synthesize the most significant literature addressing talent identification and development in futsal. Condition being studied: Talent identification and development constraints associated to: (1) the athlete; (2) the environment; (3) the task. Eligibility criteria: The publications included in the first search round met the following criteria: (1) contained relevant data concerning talent identification and/or development; (2) were performed on male futsal players; (3) were empirical studies, and; (4) were written in the English, Spanish and Portugues
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Bando, Rosangela, Florencia López Bóo, and Xia Li. Sex-Differences in Language and Socio-emotional Skills in Early Childhood. Inter-American Development Bank, 2016. http://dx.doi.org/10.18235/0011759.

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This study explores sex differences in language and socio-emotional skills. It focuses on children 7 months old to 6 years old in Chile in 2012 and Nicaragua in 2013. A focus on young children allowed for ruling out a set of environmental and identity effects to explain the gap. Females had an advantage in both countries and both dimensions. Males in Chile scored at -0.13 standard deviations (SD) in language in the distribution of females. In addition, males scored at -0.20 SD in socio-emotional skills. The gaps in Nicaragua were not statistically different to those in Chile. Thus geographical
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Luo, Xiaqin, and Luyao Chen. Speech and language features applied to the identification of patients with cognitive impairment: A systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.3.0022.

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Avis, Rupert. Annotated Bibliography of the Latest Scientific Evidence on Mpox. Institute of Development Studies, 2025. https://doi.org/10.19088/k4dd.2025.055.

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This annotated bibliography provides an overview of the latest scientific evidence on Mpox. It applied a structured approach to literature identification, utilising a search strategy that involved the terms outlined in the footnote and the date range indicated below and included only English language sources.
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Chong, Alberto E. Does It Matter How People Speak? Inter-American Development Bank, 2006. http://dx.doi.org/10.18235/0010970.

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Language serves two key functions. It enables communication between agents, which allows for the establishment and operation of formal and informal institutions. It also serves a less obvious function, a reassuring quality more closely related to issues linked with trust, social capital, and cultural identification. While research on the role of language as a learning process is widespread, there is no evidence on the role of language as a signal of cultural affinity. I pursue this latter avenue of research and show that subtle language affinity is positively linked with change in earnings whe
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Carlsson, Magnus, Stefan Eriksson, and Dan-Olof Rooth. Language Proficiency and Hiring of Immigrants: Evidence from a New Field Experimental Approach. Linnaeus University, School of Business and Economics, Department of Economics and Statistics., 2023. http://dx.doi.org/10.15626/ns.wp.2023.1.

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Labor markets in advanced economies have undergone substantial change in recentdecades due to globalization, technological improvements, and organizational changes. Due tothese developments, oral and written language skills have become increasingly important evenin less skilled jobs. Immigrants – who often have limited skills in the host country languageupon arrival – are likely to be particularly affected by the increase in language requirements.Despite this increase in literacy requirements, little is known about how immigrants’ languageproficiency is rewarded in the labor market. However, e
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Pons, Aina, Annalisa Hauck, and Tarek Abdel Aziz. On Indocyanine Green Fluorescence and Autofluorescence in thyroid and parathyroid surgery: A systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.2.0067.

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Review question / Objective: Autofluorescence (AF) and Indocyanine Green Fluorescence (ICG) were used for the first time for parathyroid gland (PG) identification in 2011 and 2015, respectively, during thyroidectomy/parathyroidectomy. Authors reported promising results. We aim to understand the efficacy, technical challenges, cost-effectiveness, and impact on postoperative biochemical and clinical outcomes of such new techniques. Eligibility criteria: The language filter was set to allow for publications in English, German, Spanish, and French assessing the use of ICG and/or AF for PG identifi
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Ricca, Bernard. Nonlinear Time Series Analyses (Part II). Instats Inc., 2024. https://doi.org/10.61700/0emwhpkidie951390.

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This four-day seminar delves into phenomenological modeling of time series, focusing on nonlinear dynamic methodologies such as sparse identification of nonlinear dynamics, dynamic mode decomposition, and hidden Markov models, all implemented using the R programming language. Participants will enhance their research skills by learning to dynamically model, analyze, and interpret time-dependent data, ultimately enabling them to conduct innovative and robust research across various fields.
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