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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5...1.219 Hits 1 – 20 of 24.379 1 Dynamic functional brain network connectivity during pseudoword processing relates to children’s reading skill Panda, Erin J.; Valiante, Taufik A.; Pang, Elizabeth W.. - : Elsevier, 2022 BASE Show details 2 Regional variation in British English voice quality Gold, Erica; Kirchhübel, Christin; Earnshaw, Kate... In: English world-wide. - Amsterdam [u.a.] : Benjamins 43 (2022) 1, 96-123 BLLDB Show details 3 An Overview of Indian Spoken Language Recognition from Machine Learning Perspective Dey, Spandan; Sahidullah, Md; Saha, Goutam In: ISSN: 2375-4699 ; EISSN: 2375-4702 ; ACM Transactions on Asian and Low-Resource Language Information Processing ; https://hal.inria.fr/hal-03616853 ; ACM Transactions on Asian and Low-Resource Language Information Processing, ACM, In press, ⟨10.1145/3523179⟩ (2022) Abstract: International audience ; Automatic spoken language identification (LID) is a very important research field in the era of multilingual voice-command-based human-computer interaction (HCI). A front-end LID module helps to improve the performance of many speech-based applications in the multilingual scenario. India is a populous country with diverse cultures and languages. The majority of the Indian population needs to use their respective native languages for verbal interaction with machines. Therefore, the development of efficient Indian spoken language recognition systems is useful for adapting smart technologies in every section of Indian society. The field of Indian LID has started gaining momentum in the last two decades, mainly due to the development of several standard multilingual speech corpora for the Indian languages. Even though significant research progress has already been made in this field, to the best of our knowledge, there are not many attempts to analytically review them collectively. In this work, we have conducted one of the very first attempts to present a comprehensive review of the Indian spoken language recognition research field. In-depth analysis has been presented to emphasize the unique challenges of low-resource and mutual influences for developing LID systems in the Indian contexts. Several essential aspects of the Indian LID research, such as the detailed description of the available speech corpora, the major research contributions, including the earlier attempts based on statistical modeling to the recent approaches based on different neural network architectures, and the future research trends are discussed. This review work will help assess the state of the present Indian LID research by any active researcher or any research enthusiasts from related fields. Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]; [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; [SCCO.LING]Cognitive science/Linguistics; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]; acoustic phonetics; code-switching; corpora development; discriminative model; Indian language identification; Language resources; language similarity; Machine learning; Signal processing systems Low-resourced languages URL: https://hal.inria.fr/hal-03616853/file/TALLIP_Overview.pdf https://doi.org/10.1145/3523179 https://hal.inria.fr/hal-03616853 https://hal.inria.fr/hal-03616853/document BASE Hide details 4 СТИЛИСТИЧЕСКИЕ РЕСУРСЫ РАЗГОВОРНОЙ РЕЧИ В РАССКАЗАХ В.М. ШУКШИНА ... : STYLISTIC RESOURCES OF COLLOQUIAL SPEECH IN V.M. SHUKSHIN’S STORIES ... А.М. Коняшкин; А.А. Коняшкин. - : Мир науки, культуры, образования, 2022 BASE Show details 5 Corpus of Japanese Telephone Conversation at Hiroshima University : Design and Current Status 五十嵐 陽介; 廣川 純子; Yosuke IGARASHI. - : 国立国語研究所, 2022 BASE Show details 6 The phonetics and phonology of Hong Kong English: a study of fricatives Ho, S.Y.B. (Sin). - 2022 BASE Show details 7 Variation in Spanish/s: Overview and New Perspectives Núñez-Méndez, Eva In: World Languages and Literatures Faculty Publications and Presentations (2022) BASE Show details 8 ИННОВАЦИОННЫЕ МЕТОДЫ ПРЕПОДАВАНИЯ ЯЗЫКОЗНАНИЯ В ГРУППАХ С РУССКИМ ЯЗЫКОМ ОБУЧЕНИЯ ... : INNOVATIVE METHODS OF TEACHING LANGUAGE IN RUSSIAN LANGUAGE TEACHING GROUPS ... Носирова, Мубина Олимовна. - : Oriental renaissance: Innovative, educational, natural and social sciences, 2022 BASE Show details 9 INNOVATIVE TEACHING METHODS TO DEVELOP CHINESE STUDENTS' ABILITY TO LEARN RUSSIAN PHONETICS ... Jiang, Y.. - : Инфинити, 2022 BASE Show details 10 Частые ошибки русскоязычных студентов в изучении фонетики китайского языка. Часть 2 ... : Common errors of Russian-speaking students in the study of Chinese phonetics. Part 2 ... Курт Ульяна Юрьевна. - : Modern oriental studies, 2022 BASE Show details 11 Paradigm uniformity effects on French liaison ... Storme, Benjamin. - : Zenodo, 2022 BASE Show details 12 Paradigm uniformity effects on French liaison ... Storme, Benjamin. - : Zenodo, 2022 BASE Show details 13 Suprasegmental Characteristics of Spontaneous Speech (Hazan et al., 2016) ... Hazan, Valerie; Tuomainen, Outi; Pettinato, Michèle. - : ASHA journals, 2022 BASE Show details 14 Nasal rustle perception without secretion bubbling (Oren et al., 2022) ... Oren, Liran; Kummer, Ann W.; Boyce, Suzanne. - : ASHA journals, 2022 BASE Show details 15 Intoxication and pitch control in tonal and non-tonal language speakers ... Chang, Charles. - : Open Science Framework, 2022 BASE Show details 16 Nasal rustle perception without secretion bubbling (Oren et al., 2022) ... Oren, Liran; Kummer, Ann W.; Boyce, Suzanne. - : ASHA journals, 2022 BASE Show details 17 Materials for Tang et al. (2022) ... Chang, Charles. - : Open Science Framework, 2022 BASE Show details 18 Suprasegmental Characteristics of Spontaneous Speech (Hazan et al., 2016) ... Hazan, Valerie; Tuomainen, Outi; Pettinato, Michèle. - : ASHA journals, 2022 BASE Show details 19 Dataset for Tang et al. (2022) ... Chang, Charles. - : Open Science Framework, 2022 BASE Show details 20 Siegerländer Sprachatlas ... Solau-Riebel, Petra. - : Universitätsbibliothek Siegen, 2022 BASE Show details Page: 1 2 3 4 5...1.219

Mobile view All Catalogues UB Frankfurt Linguistik 2.873 IDS Mannheim 262 OLC Linguistik 978 UB Frankfurt Retrokatalog 0 DNB Subject Category Language 18 Institut für Empirische Sprachwissenschaft 1.602 Leibniz-Centre General Linguistics (ZAS) 470 Bibliographies BLLDB 7.627 BDSL 9 IDS Bibliografie zur deutschen Grammatik 380 IDS Bibliografie zur Gesprächsforschung 0 IDS Konnektoren im Deutschen 0 IDS Präpositionen im Deutschen 0 IDS OBELEX meta 13 MPI-SHH Linguistics Collection 193 MPI for Psycholinguistics 74 Linked Open Data catalogues Annohub 0 Online resources Link directory 1.335 Journal directory 218 Database directory 80 Dictionary directory 33 Open access documents BASE 11.939 Linguistik-Repository 219 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0