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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 Hits 1 – 20 of 28 1 Multilingual Audio-Visual Smartphone Dataset And Evaluation ... Mandalapu, Hareesh; N, Aravinda Reddy P; Ramachandra, Raghavendra. - : arXiv, 2021 BASE Show details 2 Multilingual and Multimode Phone Recognition System for Indian Languages ... Tripathi, Kumud; Reddy, M. Kiran; Rao, K. Sreenivasa. - : arXiv, 2019 BASE Show details 3 Speech recognition using articulatory and excitation source features Rao, K Sreenivasa; K E, Manjunath. - : Springer, 2017 BASE Show details 4 Source and system features for phone recognition Manjunath, K. E.; Rao, K. Sreenivasa In: International journal of speech technology. - Boston, Mass. [u.a.] : Kluwer Acad. Publ. 18 (2015) 2, 257-270 BLLDB Show details 5 Language identification using excitation source features Rao, K Sreenivasa; Nandi, Dipanjan. - : Springer, 2015 BASE Show details 6 Language identification using spectral and prosodic features Rao, K Sreenivasa; Reddy, V Ramu; Maity, Sudhamay. - : Springer, 2015 Abstract: This book discusses the impact of spectral features extracted from frame level, glottal closure regions, and pitch-synchronous analysis on the performance of language identification systems. In addition to spectral features, the authors explore prosodic features such as intonation, rhythm, and stress features for discriminating the languages. They present how the proposed spectral and prosodic features capture the language specific information from two complementary aspects, showing how the development of language identification (LID) system using the combination of spectral and prosodic features will enhance the accuracy of identification as well as improve the robustness of the system. This book provides the methods to extract the spectral and prosodic features at various levels, and also suggests the appropriate models for developing robust LID systems according to specific spectral and prosodic features. Finally, the book discuss about various combinations of spectral and prosodic features, and the desired models to enhance the performance of LID systems. Keyword: Engineering URL: http://cds.cern.ch/record/2005811 https://doi.org/10.1007/978-3-319-17163-0 BASE Hide details 7 Segmentation, indexing and retrieval of TV broadcast news bulletins using Gaussian mixture models and vector quantization codebooks Rao, K. Sreenivasa; Pachpande, Ketan In: International journal of speech technology. - Boston, Mass. [u.a.] : Kluwer Acad. Publ. 17 (2014) 3, 259-269 OLC Linguistik Show details 8 Film segmentation and indexing using autoassociative neural networks Rao, K. Sreenivasa; Nandi, Dipanjan; Koolagudi, Shashidhar G. In: International journal of speech technology. - Boston, Mass. [u.a.] : Kluwer Acad. Publ. 17 (2014) 1, 65-74 OLC Linguistik Show details 9 Two-stage intonation modeling using feedforward neural networks for syllable based text-to-speech synthesis Reddy, V. Ramu; Rao, K. Sreenivasa In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 27 (2013) 5, 1105-1126 OLC Linguistik Show details 10 Emotion recognition from speech using global and local prosodic features Rao, K. Sreenivasa; Koolagudi, Shashidhar G.; Vempada, Ramu Reddy In: International journal of speech technology. - Boston, Mass. [u.a.] : Kluwer Acad. Publ. 16 (2013) 2, 143-160 OLC Linguistik Show details 11 Vowel onset point detection for noisy speech using spectral energy at formant frequencies Vuppala, Anil Kumar; Rao, K. Sreenivasa In: International journal of speech technology. - Boston, Mass. [u.a.] : Kluwer Acad. Publ. 16 (2013) 2, 229-235 OLC Linguistik Show details 12 Pitch synchronous and glottal closure based speech analysis for language recognition Rao, K. Sreenivasa; Maity, Sudhamay; Reddy, V. Ramu In: International journal of speech technology. - Boston, Mass. [u.a.] : Kluwer Acad. Publ. 16 (2013) 4, 413-430 OLC Linguistik Show details 13 Non-uniform time scale modification using instants of significant excitation and vowel onset points Rao, K. Sreenivasa; Vuppala, Anil Kumar In: Speech communication. - Amsterdam [u.a.] : Elsevier 55 (2013) 6, 745-756 OLC Linguistik Show details 14 Robust emotion recognition using spectral and prosodic features Rao, K. Sreenivasa; Koolagudi, Shashidhar G.. - New York, NY [u.a.] : Springer, 2013 BLLDB UB Frankfurt Linguistik Show details 15 Emotion Recognition using Speech Features Koolagudi, Shashidhar G; Rao, K Sreenivasa. - : Springer, 2013 BASE Show details 16 Robust emotion recognition using spectral and prosodic features Rao, K Sreenivasa; Koolagudi, Shashidhar G. - : Springer, 2013 BASE Show details 17 Emotion recognition from speech: a review Rao, K. Sreenivasa; Koolagudi, Shashidhar G. In: International journal of speech technology. - Boston, Mass. [u.a.] : Kluwer Acad. Publ. 15 (2012) 2, 99-117 BLLDB OLC Linguistik Show details 18 Emotion recognition from speech using source, system, and prosodic features Rao, K. Sreenivasa; Koolagudi, Shashidhar G. In: International journal of speech technology. - Boston, Mass. [u.a.] : Kluwer Acad. Publ. 15 (2012) 2, 265-289 BLLDB OLC Linguistik Show details 19 Predicting Prosody from Text for Text-to-Speech Synthesis Rao, K Sreenivasa. - : Springer, 2012 BASE Show details 20 Development of syllable-based text to speech synthesis system in Bengali Ghosh, Krishnendu; Rao, K. Sreenivasa; Maity, Sudhamay... In: International journal of speech technology. - Boston, Mass. [u.a.] : Kluwer Acad. Publ. 14 (2011) 3, 167-181 BLLDB OLC Linguistik Show details Page: 1 2

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