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Статті в журналах з теми "Tamil speech recognition"
Rojathai, S., and M. Venkatesulu. "Investigation of ANFIS and FFBNN Recognition Methods Performance in Tamil Speech Word Recognition." International Journal of Software Innovation 2, no. 2 (April 2014): 43–53. http://dx.doi.org/10.4018/ijsi.2014040103.
Повний текст джерелаRojathai, S., and M. Venkatesulu. "Tamil Speech Word Recognition System with Aid of ANFIS and Dynamic Time Warping (DTW)." Journal of Computational and Theoretical Nanoscience 13, no. 10 (October 1, 2016): 6719–27. http://dx.doi.org/10.1166/jctn.2016.5619.
Повний текст джерелаNelapati, Ratna Kanth, and Saraswathi Selvarajan. "Affect Recognition in Human Emotional Speech using Probabilistic Support Vector Machines." International Journal on Recent and Innovation Trends in Computing and Communication 10, no. 2s (December 31, 2022): 166–73. http://dx.doi.org/10.17762/ijritcc.v10i2s.5924.
Повний текст джерелаHashim Changrampadi, Mohamed, A. Shahina, M. Badri Narayanan, and A. Nayeemulla Khan. "End-to-End Speech Recognition of Tamil Language." Intelligent Automation & Soft Computing 32, no. 2 (2022): 1309–23. http://dx.doi.org/10.32604/iasc.2022.022021.
Повний текст джерелаThangarajan, R., A. M. Natarajan, and M. Selvam. "Syllable modeling in continuous speech recognition for Tamil language." International Journal of Speech Technology 12, no. 1 (March 2009): 47–57. http://dx.doi.org/10.1007/s10772-009-9058-0.
Повний текст джерелаSuriya, Dr S., S. Nivetha, P. Pavithran, Ajay Venkat S., Sashwath K. G., and Elakkiya G. "Effective Tamil Character Recognition Using Supervised Machine Learning Algorithms." EAI Endorsed Transactions on e-Learning 8, no. 2 (February 8, 2023): e1. http://dx.doi.org/10.4108/eetel.v8i2.3025.
Повний текст джерелаSarkar, Swagata, Sanjana R, Rajalakshmi S, and Harini T J. "Simulation and detection of tamil speech accent using modified mel frequency cepstral coefficient algorithm." International Journal of Engineering & Technology 7, no. 3.3 (June 8, 2018): 426. http://dx.doi.org/10.14419/ijet.v7i2.33.14202.
Повний текст джерелаGeetha, K., and R. Vadivel. "Phoneme Segmentation of Tamil Speech Signals Using Spectral Transition Measure." Oriental journal of computer science and technology 10, no. 1 (March 4, 2017): 114–19. http://dx.doi.org/10.13005/ojcst/10.01.15.
Повний текст джерелаA, Akila, and Chandra E. "WORD BASED TAMIL SPEECH RECOGNITION USING TEMPORAL FEATURE BASED SEGMENTATION." ICTACT Journal on Image and Video Processing 5, no. 4 (May 1, 2015): 1037–43. http://dx.doi.org/10.21917/ijivp.2015.0152.
Повний текст джерелаKalamani, M., M. Krishnamoorthi, and R. S. Valarmathi. "Continuous Tamil Speech Recognition technique under non stationary noisy environments." International Journal of Speech Technology 22, no. 1 (November 30, 2018): 47–58. http://dx.doi.org/10.1007/s10772-018-09580-8.
Повний текст джерелаДисертації з теми "Tamil speech recognition"
Lin, Wei-Ting, and 林威廷. "A Design of Trilingual Speech Recognition System for Chinese, Turkish and Tamil." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/83040195001830259860.
Повний текст джерела國立中山大學
電機工程學系研究所
100
In this thesis, both Turkish and Tamil, a language spoken in southern India and Sri Lanka, are studied in addition to Mandarin Chinese. It is hoped that the history, culture, and economy behind each language can be acquainted, tasted and appreciated during the learning process. In the ancient Chinese Han and Tang Dynasties, the “Silk Road” played the most magnificent role to connect among the Oriental China, the Western Turkey and the Southern India as the international trading corridor. In this modern era, Turkey and India are both the most important cotton exporting countries. Moreover, China, Turkey and India have been showing their potential to the newly emerging markets in the world. Therefore, a trilingual speech recognition system is developed and implemented to help us to learn Chinese, Turkish and Tamil, as well as to enhance our understanding to their history and culture. In this trilingual system, linear predicted cepstral coefficients, Mel-frequency cepstral coefficients, hidden Markov model and phonotactics are used as the two syllable feature models and the recognition model respectively. For the Chinese system, a 2,699 two-syllable words database is used as the training corpus. For the Turkish and Tamil systems, a database of 10 utterances per mono-syllable is established by applying their pronunciation rules. These 10 utterances are collected through reading 5 rounds of the same mono-syllables twice with tone 1 and tone 4. The correct rates of 88.30%, 84.21%, and 88.74% can be reached for the 82,000 Chinese, 30,795 Turkish, and 3,500 Tamil phrase databases respectively. The computation time for each system is within 1.5 seconds. Furthermore, a trilingual language-speech recognition system for 300 common words, composed of 100 words from each language, is developed. A 98% correct language-phrase recognition rate can be reached with the computation time less than 2 seconds.
Частини книг з теми "Tamil speech recognition"
Sowmya, V., and A. Rajeswari. "Speech Emotion Recognition for Tamil Language Speakers." In Machine Intelligence and Signal Processing, 125–36. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1366-4_10.
Повний текст джерелаSaraswathi, S., and T. V. Geetha. "Building Language Models for Tamil Speech Recognition System." In Lecture Notes in Computer Science, 161–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30176-9_21.
Повний текст джерелаSaraswathi, S., and T. V. Geetha. "Implementation of Tamil Speech Recognition System Using Neural Networks." In Lecture Notes in Computer Science, 169–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30176-9_22.
Повний текст джерелаSrikanth, M., D. Pravena, and D. Govind. "Tamil Speech Emotion Recognition Using Deep Belief Network(DBN)." In Advances in Intelligent Systems and Computing, 328–36. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67934-1_29.
Повний текст джерелаGirirajan, S., and A. Pandian. "Convolutional Neural Network Based Automatic Speech Recognition for Tamil Language." In Lecture Notes in Electrical Engineering, 91–103. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4831-2_8.
Повний текст джерелаBetina, Antony J., Paul N. R. Rejin, and G. S. Mahalakshmi. "Applying entity recognition and verb role labelling for information extraction of Tamil biomedicine." In Artificial Intelligence and Speech Technology, 211–20. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003150664-24.
Повний текст джерелаKarpagavalli, S., R. Deepika, P. Kokila, K. Usha Rani, and E. Chandra. "Isolated Tamil Digit Speech Recognition Using Template-Based and HMM-Based Approaches." In Communications in Computer and Information Science, 441–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29216-3_48.
Повний текст джерелаPrayla Shyry, S., A. Christy, and Y. Bevish Jinila. "Speech Emotion Recognition of Tamil Language: An Implementation with Linear and Nonlinear Feature." In Lecture Notes in Electrical Engineering, 145–54. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9154-6_15.
Повний текст джерелаAkanksha, Akanksha. "Tamil Language Automatic Speech Recognition Based on Integrated Feature Extraction and Hybrid Deep Learning Model." In Lecture Notes in Networks and Systems, 283–92. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9719-8_23.
Повний текст джерелаVimala, C., and V. Radha. "Efficient Speaker Independent Isolated Speech Recognition for Tamil Language Using Wavelet Denoising and Hidden Markov Model." In Lecture Notes in Electrical Engineering, 557–69. India: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1000-9_52.
Повний текст джерелаТези доповідей конференцій з теми "Tamil speech recognition"
R., Kiran, Nivedha K., Pavithra Devi S., and Subha T. "Voice and speech recognition in Tamil language." In 2017 2nd International Conference on Computing and Communications Technologies (ICCCT). IEEE, 2017. http://dx.doi.org/10.1109/iccct2.2017.7972293.
Повний текст джерелаAkhilesh, A., Brinda P, Keerthana S, Deepa Gupta, and Susmitha Vekkot. "Tamil Speech Recognition Using XLSR Wav2Vec2.0 & CTC Algorithm." In 2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2022. http://dx.doi.org/10.1109/icccnt54827.2022.9984422.
Повний текст джерелаHarish, S., P. Vijayalakshmi, and T. Nagarajan. "Significance of segmentation in phoneme based Tamil speech recognition system." In 2011 3rd International Conference on Electronics Computer Technology (ICECT). IEEE, 2011. http://dx.doi.org/10.1109/icectech.2011.5941739.
Повний текст джерелаGanesh, Akila A., and Chandra Ravichandran. "Grapheme Gaussian model and prosodic syllable based Tamil speech recognition system." In 2013 International Conference on Signal Processing and Communication (ICSC). IEEE, 2013. http://dx.doi.org/10.1109/icspcom.2013.6719821.
Повний текст джерелаSaraswathi, S., and T. V. Geetha. "Two Level Language Models for Improving the Performance of Tamil Speech Recognition." In International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007). IEEE, 2007. http://dx.doi.org/10.1109/iccima.2007.28.
Повний текст джерелаKarpagavalli, S., and E. Chandra. "Phoneme and word based model for tamil speech recognition using GMM-HMM." In 2015 International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2015. http://dx.doi.org/10.1109/icaccs.2015.7324119.
Повний текст джерелаChengalvarayan, Rathinavelu. "The use of nonlinear energy transformation for Tamil connected-digit speech recognition." In 6th International Conference on Spoken Language Processing (ICSLP 2000). ISCA: ISCA, 2000. http://dx.doi.org/10.21437/icslp.2000-733.
Повний текст джерелаRadha, V., C. Vimala, and M. Krishnaveni. "Continuous Speech Recognition system for Tamil language using monophone-based Hidden Markov Model." In the Second International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2393216.2393255.
Повний текст джерелаRam, C. Sunitha, and R. Ponnusamy. "An effective automatic speech emotion recognition for Tamil language using Support Vector Machine." In 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT). IEEE, 2014. http://dx.doi.org/10.1109/icicict.2014.6781245.
Повний текст джерелаMadhavaraj, A., and A. G. Ramakrishnan. "Design and development of a large vocabulary, continuous speech recognition system for Tamil." In 2017 14th IEEE India Council International Conference (INDICON). IEEE, 2017. http://dx.doi.org/10.1109/indicon.2017.8488025.
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