Gotowe bibliografie tematyczne / Unlimited vocabulary

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Gotowa bibliografia na temat „Unlimited vocabulary”

Autor: Grafiati

Data publikacji: 6 września 2023

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Artykuły w czasopismach na temat "Unlimited vocabulary"

van de Goor, A. J., i G. J. Nanninga. "Speech synthesis system with unlimited vocabulary for the Dutch language". Microprocessing and Microprogramming 24, nr 1-5 (sierpień 1988): 325–33. http://dx.doi.org/10.1016/0165-6074(88)90073-7.

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Nagendar, Gattigorla, Viresh Ranjan, Gaurav Harit i C. Jawahar. "Efficient Query Specific DTW Distance for Document Retrieval with Unlimited Vocabulary". Journal of Imaging 4, nr 2 (8.02.2018): 37. http://dx.doi.org/10.3390/jimaging4020037.

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Hirsimäki, Teemu, Mathias Creutz, Vesa Siivola, Mikko Kurimo, Sami Virpioja i Janne Pylkkönen. "Unlimited vocabulary speech recognition with morph language models applied to Finnish". Computer Speech & Language 20, nr 4 (październik 2006): 515–41. http://dx.doi.org/10.1016/j.csl.2005.07.002.

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Santi Devi. "Kosa Kata Baru dalam Bahasa Indonesia (Analisis Peneliti Terdahulu Menggunakan Kajian Kualitatif dalam Penggunaan Kosakata Baru Menjadi Bahasa Baku)". Jurnal Mahasiswa Kreatif 1, nr 1 (30.01.2023): 01–04. http://dx.doi.org/10.59581/jmk-widyakarya.v1i1.121.

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Changes in the meaning of words can occur because of the need to accommodate a concept that does not yet have a vocabulary or a concept that has the same component of meaning as a vocabulary that already existed. For example, the use of the word broadcast 'spread'. Originally the meaning of the word broadcast was synonymous with the function of radio, but now it is also used to define other transmissions such as broadcasting counterfeit money. The development of the vocabulary of a language can also show the socio-cultural development of its speakers. This development is unlimited: it will always develop as long as the speakers are still there and use Indonesian in everyday life.

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Omar, Umazah, i Aizan Yaacob. "Exploring Types of Vocabulary Learning Strategies used by TESL Teacher Trainees at The Institute of Teachers Education". South Asian Journal of Social Sciences and Humanities 2, nr 4 (2021): 102–16. http://dx.doi.org/10.48165/sajssh.2021.2407.

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Vocabulary is described as an essential element in second language learning. Having a good command over vocabulary helps in gaining unlimited access to latest information available at different platforms. Therefore, improving vocabulary through Vocabulary Learning Strategies (VLSs) will help the second language learners to become, academically and communicatively, more successful. The present study investigated the types of vocabulary learning strategies used by teacher trainees majoring in Teaching English as a Second Language (TESL) at the Institute for Teachers Education (ITEs) Darulaman Campus. Vocabulary learning strategies or skills are not directly taught to TESL teacher trainees during their training at ITEs. Teaching and learning vocabulary strategies are neglected by most of the teacher trainees. However, they need to make their teaching and learning processes more successful while learning a second language. This study was conducted based on the theories related to second language acquisition and used qualitative approach using the structured interviews of 14 TESL teacher trainees. The findings of the study were analysed based on Gu and Johnson’s (1996) and Schmitt (1996) categorisation of Vocabulary Learning Strategies and the results revealed TESL teacher trainees employed more metacognitive strategies in their vocabulary learning compared to other nine VLSs.

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Webb, Stuart, i Anna Piasecki. "Re-examining the effects of word writing on vocabulary learning". Approaches to learning, testing, and researching L2 vocabulary 169, nr 1 (16.04.2018): 72–94. http://dx.doi.org/10.1075/itl.00007.web.

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Abstract This study investigated the effects of word writing on vocabulary learning by comparing three conditions in which there was (a) limited time to write words, (b) unlimited time to write words, and (c) a non-writing word-picture pairs comparison. Non-native speakers studying English as a second language encountered 8 word-picture pairs in each condition and were administered a test measuring form recall and another measuring receptive knowledge of written form. The results indicated that there was little difference between scores on both tests when time on task was the same. However, when the participants had as much time as they needed to write and learn words they had higher scores on both dependent measures than when learning in the other two conditions. The findings suggest that an ecologically valid approach to word writing may facilitate vocabulary learning.

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Fagyal, Zsuzsanna. "Phonetics and speaking machines". Historiographia Linguistica 28, nr 3 (31.12.2001): 289–330. http://dx.doi.org/10.1075/hl.28.3.02fag.

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Summary This paper shows that in the 17th century various attempts were made to build fully automatic speaking devices resembling those exhibited in the late 18th-century in France and Germany. Through the analysis of writings by well-known 17th-century scientists, and a document hitherto unknown in the history of phonetics and speech synthesis, an excerpt from La Science universelle (1667[1641]) of the French writer Charles Sorel (1599–1674), it is argued that engineers and scientists of the Baroque period have to be credited with the first model of multilingual text-to-speech synthesis engines using unlimited vocabulary.

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Yarovikova, Y. V., i E. A. Balygina. "The Implementation of the Principle of Economy in the Formation of Psychological Terms in English and Russian". Язык и текст 7, nr 2 (2020): 12–19. http://dx.doi.org/10.17759/langt.2020070202.

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The paper addresses the ways of applying economy principle to the sublanguage of psychology. The authors identify the most productive term formation methods, which show the tendency of both languages to compression of nominal words and phrases. In the system of psychological terms of the English language, the most productive ways of linguistic compression are affixation and compounding. The English terminological system is rich, functional and economical because of its unlimited potential for compounding and affixation. The Russian terminological system is more likely to enrich the vocabulary through phonetic borrowings, semantic derivation and calque. It is argued that the borrowings acquired by the Russian terminological system account for the multitude of synonymous terms. On the other hand, phonetic borrowings and semantic calque have enriched the vocabulary without effort and redundancy. It is concluded that economy principle plays a fundamental role in the creation of new words and their adaptation to the English and Russian terminological systems.

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Boyko, Yuliya, Yulia Kupchyshyna, Olga Tarasova, Ievgen Dolynskiy i Ihor Roskvas. "Current trends in english public speech translation (based on TED talks platform)". Revista Amazonia Investiga 12, nr 62 (30.03.2023): 312–18. http://dx.doi.org/10.34069/ai/2023.62.02.31.

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Nowadays, the media is rapidly developing, and messaging processes are inexhaustible thanks to the Internet. Audiovisual content has become a separate form of communication and learning. This document analyzes the popular TED Talks platform, describes its use with interpretation students, and shows the research results of students using TED Talks on translation trends for public speaking. The document uses the potential of TED Talks as an unlimited source of knowledge, information, ideas, and inspiration. The use of speeches as methodologically sound and authentic English material has improved listening skills, as well as pronunciation and spelling through the ability to read active subtitles and scripts, and develop and enrich students' vocabulary.

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Gitsaki, Christina, i Richard P. Taylor. "Internet-based activities for the ESL classroom". ReCALL 11, nr 1 (maj 1999): 47–57. http://dx.doi.org/10.1017/s0958344000002081.

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The Internet offers a wealth of information and unlimited resources that teachers can use in order to expose students to authentic language use. Exposure, however, is not enough to trigger language acquisition. Students need to be involved in tasks that integrate the use of computers and enhance language acquisition. This paper outlines an instructional system designed to guide English as a Second Language (ESL) students through their exploration of the Internet and carry out projects that will ultimately help them improve their reading and writing skills and enrich their vocabulary. Through this instructional system the benefits of using the Internet for ESL purposes with different types of students in different educational environments can be maximised.

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Rozprawy doktorskie na temat "Unlimited vocabulary"

Madhavaraj, A. "Strategies for Handling Large Vocabulary and Data Sparsity Problems for Tamil Speech Recognition". Thesis, 2020. https://etd.iisc.ac.in/handle/2005/4759.

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This thesis focuses on the design and development of every building block of a very large vocabulary, continuous speech recognition (LVCSR) system and various experiments conducted in order to enhance its performance. To our knowledge, this is the first report of development of such a full-fledged Tamil LVCSR system, since we could not find any journal or even refereed conference papers building a Tamil LVCSR system and reporting recognition results on large scale open-source speech recognition test datasets. A large read speech corpus of 217 hours has been collected and annotated at the sentence level for the development of the LVCSR system. Out of this, 160 hours of data has been used for training the LVCSR, 50 hours as the test set, and the publicly available 7 hours of OpenSLR-65 data released by Google is used as the development set. The major contributions of the thesis are: • Collection of a large amount of Tamil speech and text data, editing the transcriptions to match the spoken utterances and using them to develop a deep neural network (DNN) and graphical model-based Tamil LVCSR system. • Handling the unlimited vocabulary problem in Tamil by proposing subword modeling technique using novel subword dictionary creation and word segmentation techniques implemented efficiently using weighted finite state transducer (WFST) framework. • Addressing the data sparsity problem by leveraging data from multiple low and medium resourced languages by pooling data using novel phone/senone mapping techniques and training a multitask DNN (MT-DNN). • Proposing a novel coactivation loss for speaker-adapting the DNN using asymptotic Bayesian approximation through Laplace approximation, by using mean and covariance statistics of the activation values at all the hidden layers of the speaker-independent DNN. • Studying the use of scattering transform features in acoustic modeling and proposing a DNN architecture inspired by it to jointly perform feature extraction and acoustic modeling from raw speech signal. The first part of the thesis addresses the most important problem of unlimited vocabulary in Tamil and the effective techniques proposed based on subword modeling strategies to address it. The morphology, agglutination and inflection properties of Tamil language give rise to the problem of unlimited vocabulary. A graphical model based speech recognition system requires a finite set of vocabulary; however, it is impossible to contain even the most commonly used words in Tamil within a finite set. We propose and implement various techniques based on maximum likelihood (using expectation-maximization algorithm) and Viterbi estimation techniques to segment each word into its constituent subwords and use them in our recognition framework. We have also used morphological analyzers and manually created graphical models for word segmentation. Using these subword sequences, we construct lexicon and grammar graphs in a specific way so that we address the unlimited vocabulary problem to a large extent with only a limited amount of post-processing at the output stage of the recognition engine. The proposed methods are highly effective in reducing the out-of-vocabulary words in the test corpus from 10.73% to 1.68% and reducing the word error rate from 24.7% to 12.31%. In the second part of the thesis, we address the data sparsity problem using multilingual training of DNN-based acoustic model by leveraging acoustic information from the transcribed speech corpora of other languages. These experiments are carried out in a limited resource setting, for which we have proposed two techniques. In the proposed data pooling with phone/senone mapping technique, we train the DNN acoustic model with features and senones from the target as well as the source languages by pooling them together. Since the phone sets are different for the source and target languages, we map the phone set in the source language to that of the target language before training the network. In the second approach proposed, a MT-DNN is trained with features from the source as well as target languages to predict the senones of each language in separate output layers. We modify the cross-entropy loss function such that only those DNN layers just before the output layers that are responsible for predicting the senones of a language are updated during training, if the feature vector belongs to that language. The data pooling with DNN-based senone mapping and the MT-DNN methods give relative improvements of 9.66% and 13.94% over the baseline system, respectively. The third part of the thesis deals with the speaker adaptation challenge in a supervised manner. We have proposed techniques based on asymptotic Bayesian approximation to derive a loss function and use it to adapt the speaker-independent DNN (trained on multiple speaker data) using a limited amount of speaker-specific adaptation data. The proposed loss function uses the advantage of cross-entropy loss and it can as well be viewed as a generalization of the well known center loss function. The speaker-adapted models thus obtained for individual speakers reduces the WER from 17.33% to 13.97%. In the final part of the thesis, we study the effect of using scattering transform in the feature extraction stage of our ASR. From our experiments, we show that the scattering transform based features perform better than traditional features like mel frequency cepstral coefficients (MFCC) and log filterbank energies (LFBE). Motivated by this, we propose different DNN architectures using one-dimensional (1-D) and two-dimensional (2-D) convolution layers to predict the senones directly from the raw speech waveform. The convolution layers are initialized with 1-D and 2-D Gabor filterbank coefficients such that the intermediate layers of the DNN learn a representation similar to that of scattering transform based features. The proposed DNN architecture where the convolution layers are initialized with Gabor filter coefficients and are updated during training gives the best WER of 12.21%, which is a relative improvement of 9.42% over the baseline DNN trained using LFBE features.

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Książki na temat "Unlimited vocabulary"

Leslie, Davis. Vocabulary unlimited: Build a more powerful vocabulary. Plantation, Fla: Specialty Press, 1996.

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Vasishtha, Prakhar. Perfect English Grammar and Unlimited Vocabulary: With Rules, Exercises and Vocabulary Builder. Independently Published, 2017.

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Vasishtha, Prakhar. Unlimited Vocabulary: Have a Phenomenal Vocabulary , Learn 65% of Words in 1 Hour. Independently Published, 2017.

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Vasishtha, Prakhar. Unlimited Speed Reading: Accelerate Reading, Comprehend Better, Enhance Vocabulary. Independently Published, 2017.

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Pilla, Marianne Laino. The Best: High/Low Books for Reluctant Readers (Libraries Unlimited Data Book Series). Libraries Unlimited, 1990.

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Części książek na temat "Unlimited vocabulary"

Dermatas, E., i G. Kokkinakis. "A Multilingual Unlimited Vocabulary Stochastic Tagger". W Advanced Speech Applications, 98–106. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-85151-3_5.

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Brakensiek, Anja, Daniel Willett i Gerhard Rigoll. "Unlimited Vocabulary Script Recognition Using Character N-Grams". W Informatik aktuell, 436–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59802-9_55.

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Bajpai, Anandita. "Time and Temporalizing Tactics I". W Speaking the Nation, 85–123. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199481743.003.0003.

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Chapter 2 illustrates how in order to give currency to the reforms, the PMs conjure the idea of an idealized future. Growth is presented as a human necessity and reforms become the inevitable means to realize the dream of growth for all. India’s move to the future is presented not as an uncalculated measure, but a controlled trajectory which does not succumb to ‘unlimited capitalism’. However, behind this rhetoric emerges the category of an ‘other within’ India- large sections of Indian population who are no immediate winners of the reforms but are tranquilized, by being relegated to a “waiting room” condition. Trickle down is legitimized by informing people that they ought to wait for the benefits of the transitions to reach them. The PMs also paradoxically employ a vocabulary of the socialist past to project the future. Although what is being introduced is a drastic shift, the resources used to present the new borrow heavily from the lexicon of Nehruvian developmentalism. Thus, the new is sold by using a vocabulary which is not so new.

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Wang, Xin-Jing, Lei Zhang, Xirong Li i Wei-Ying Ma. "Annotating Images by Mining Image Search". W Machine Learning, 1066–89. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-60960-818-7.ch417.

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Although it has been studied for years by computer vision and machine learning communities, image annotation is still far from practical. In this chapter, the authors propose a novel attempt of modeless image annotation, which investigates how effective a data-driven approach can be, and suggest annotating an uncaptioned image by mining its search results. The authors collected 2.4 million images with their surrounding texts from a few photo forum Web sites as our database to support this data-driven approach. The entire process contains three steps: (1) the search process to discover visually and semantically similar search results; (2) the mining process to discover salient terms from textual descriptions of the search results; and (3) the annotation rejection process to filter noisy terms yielded by step 2. To ensure real time annotation, two key techniques are leveraged – one is to map the high dimensional image visual features into hash codes, the other is to implement it as a distributed system, of which the search and mining processes are provided as Web services. As a typical result, the entire process finishes in less than 1 second. Since no training dataset is required, our proposed approach enables annotating with unlimited vocabulary, and is highly scalable and robust to outliers. Experimental results on real Web images show the effectiveness and efficiency of the proposed algorithm.

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Streszczenia konferencji na temat "Unlimited vocabulary"

Ranjan, Viresh, Gaurav Harit i C. V. Jawahar. "Document Retrieval with Unlimited Vocabulary". W 2015 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2015. http://dx.doi.org/10.1109/wacv.2015.104.

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Kurimo, Mikko, Antti Puurula, Ebru Arisoy, Vesa Siivola, Teemu Hirsimäki, Janne Pylkkönen, Tanel Alumäe i Murat Saraclar. "Unlimited vocabulary speech recognition for agglutinative languages". W the main conference. Morristown, NJ, USA: Association for Computational Linguistics, 2006. http://dx.doi.org/10.3115/1220835.1220897.

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Hirsimäki, Teemu, i Mikko Kurimo. "Analysing recognition errors in unlimited-vocabulary speech recognition". W Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers. Morristown, NJ, USA: Association for Computational Linguistics, 2009. http://dx.doi.org/10.3115/1620853.1620906.

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Smit, Peter, Siva Reddy Gangireddy, Seppo Enarvi, Sami Virpioja i Mikko Kurimo. "Character-based units for unlimited vocabulary continuous speech recognition". W 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU). IEEE, 2017. http://dx.doi.org/10.1109/asru.2017.8268929.

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Kim, Byeongchang, WonIl Lee, Geunbae Lee i Jong-Hyeok Lee. "Unlimited vocabulary grapheme to phoneme conversion for Korean TTS". W the 36th annual meeting. Morristown, NJ, USA: Association for Computational Linguistics, 1998. http://dx.doi.org/10.3115/980845.980958.

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Kim, Byeongchang, WonIl Lee, Geunbae Lee i Jong-Hyeok Lee. "Unlimited vocabulary grapheme to phoneme conversion for Korean TTS". W the 17th international conference. Morristown, NJ, USA: Association for Computational Linguistics, 1998. http://dx.doi.org/10.3115/980451.980958.

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Yuqing Gao, Taiyi Huang, Zhiwei Lin, Bo Xu i Dongxin Xu. "A real-time Chinese speech recognition system with unlimited vocabulary". W [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1991. http://dx.doi.org/10.1109/icassp.1991.150326.

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Siivola, Vesa, Teemu Hirsimaki, Mathias Creutz i Mikko Kurimo. "Unlimited vocabulary speech recognition based on morphs discovered in an unsupervised manner". W 8th European Conference on Speech Communication and Technology (Eurospeech 2003). ISCA: ISCA, 2003. http://dx.doi.org/10.21437/eurospeech.2003-640.

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Fraga, Francisco J. "A Speech Recognition Back-End Algorithm for Portuguese Language with Unlimited Vocabulary". W 2002 International Telecommunications Symposium. Sociedade Brasileira de Telecomunicações, 2002. http://dx.doi.org/10.14209/its.2002.861.

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Altosaar, Toomas, i Matti Karjalainen. "A knowledge-based approach to unlimited vocabulary speech recognition for the Finnish language". W First European Conference on Speech Communication and Technology (Eurospeech 1989). ISCA: ISCA, 1989. http://dx.doi.org/10.21437/eurospeech.1989-311.

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Raporty organizacyjne na temat "Unlimited vocabulary"

Everett, Stephanie S. Unlimited Vocabulary Synthesis Using Line Spectrum Pairs. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 1991. http://dx.doi.org/10.21236/ada241634.

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