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Academic literature on the topic 'Waveform Concatenation Technique'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "Waveform Concatenation Technique"

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Panda, Soumya Priyadarsini, and Ajit Kumar Nayak. "A waveform concatenation technique for text-to-speech synthesis." International Journal of Speech Technology 20, no. 4 (2017): 959–76. http://dx.doi.org/10.1007/s10772-017-9463-8.

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Panda, Soumya Priyadarsini, and Ajit Kumar Nayak. "A Context-based Numeral Reading Technique for Text to Speech Systems." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (2018): 4533–44. https://doi.org/10.11591/ijece.v8i6.pp4533-4544.

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This paper presents a novel technique for context based numeral reading in Indian language text to speech systems. The model uses a set of rules to determine the context of the numeral pronunciation and is being integrated with the waveform concatenation technique to produce speech out of the input text in Indian languages. For this purpose, the three Indian languages Odia, Hindi and Bengali are considered. To analyze the performance of the proposed technique, a set of experiments are performed considering different context of numeral pronunciations and the results are compared with existing s

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Panda, Soumya Priyadarsini, and Ajit Kumar Nayak. "A Context-based Numeral Reading Technique for Text to Speech Systems." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (2018): 4533. http://dx.doi.org/10.11591/ijece.v8i6.pp4533-4544.

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This paper presents a novel technique for context based numeral reading in Indian language text to speech systems. The model uses a set of rules to determine the context of the numeral pronunciation and is being integrated with the waveform concatenation technique to produce speech out of the input text in Indian languages. For this purpose, the three Indian languages Odia, Hindi and Bengali are considered. To analyze the performance of the proposed technique, a set of experiments are performed considering different context of numeral pronunciations and the results are compared with existing s

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Tan, Choon Beng, Mohd Hanafi Ahmad Hijazi, Frazier Kok, Mohd Saberi Mohamad, and Puteri Nor Ellyza Nohuddin. "Artificial speech detection using image-based features and random forest classifier." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (2022): 161. http://dx.doi.org/10.11591/ijai.v11.i1.pp161-172.

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The ASVspoof 2015 Challenge was one of the efforts of the research community in the field of speech processing to foster the development of generalized countermeasures against spoofing attacks. However, most countermeasures submitted to the ASVspoof 2015 Challenge failed to detect the S10 attack effectively, the only attack that was generated using the waveform concatenation approach. Hence, more informative features are needed to detect previously unseen spoofing attacks. This paper presents an approach that uses data transformation techniques to engineer image-based features together with ra

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Choon, Beng Tan, Hanafi Ahmad Hijazi Mohd, Kok Frazier, Saberi Mohamad Mohd, and Nor Ellyza Nohuddin Puteri. "Artificial speech detection using image-based features and random forest classifier." International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (2022): 161–72. https://doi.org/10.11591/ijai.v11.i1.pp161-172.

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The ASVspoof 2015 Challenge was one of the efforts of the research community in the field of speech processing to foster the development of generalized countermeasures against spoofing attacks. However, most countermeasures submitted to the ASVspoof 2015 Challenge failed to detect the S10 attack effectively, the only attack that was generated using the waveform concatenation approach. Hence, more informative features are needed to detect previously unseen spoofing attacks. This paper presents an approach that uses data transformation techniques to engineer image-based features together with ra

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Pravin, M. Ghate*1 &. S.D.Shirbhadurkar2. "SPEECH SYNTHESIS USING SYLLABLE FOR MARATHI LANGUAGE." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 1 (2018): 549–56. https://doi.org/10.5281/zenodo.1158794.

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Speech synthesis is the most significant applications in linguistic communication process. The Text to Speech structure is the undertaking of accepts the input sentence and converts the audible speech as output. The Marathi language may be a syllable based language. A syllable is the unit of language, which may be spoken independent of the adjacent phones. It consists of an interrupted portion of sound, once the word is pronounced. The task of proposed Text to Speech System for Marathi language includes syllabication, Letter-to-Sound rules and concatenation. Syllabication is that the method of

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Jacob, Agnes, and P. Mythili. "Developing a Child Friendly Text-to-Speech System." Advances in Human-Computer Interaction 2008 (2008): 1–6. http://dx.doi.org/10.1155/2008/597971.

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This paper discusses the implementation details of a child friendly, good quality, English text-to-speech (TTS) system that is phoneme-based, concatenative, easy to set up and use with little memory. Direct waveform concatenation and linear prediction coding (LPC) are used. Most existing TTS systems are unit-selection based, which use standard speech databases available in neutral adult voices. Here reduced memory is achieved by the concatenation of phonemes and by replacing phonetic wave files with their LPC coefficients. Linguistic analysis was used to reduce the algorithmic complexity inste

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Zhang, Kuiyuan, Zhongyun Hua, Rushi Lan, Yifang Guo, Yushu Zhang, and Guoai Xu. "Multi-View Collaborative Learning Network for Speech Deepfake Detection." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 1 (2025): 1075–83. https://doi.org/10.1609/aaai.v39i1.32094.

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As deep learning techniques advance rapidly, deepfake speech synthesized through text-to-speech or voice conversion networks is becoming increasingly realistic, posing significant challenges for detection and raising potential threats to social security. This growing realism has prompted extensive research in speech deepfake detection. However, current detection methods primarily focus on extracting features from either the raw waveform or the spectrogram, often overlooking the valuable correspondences between these two modalities that could enhance the detection of previously unseen types of

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"Text to Speech Synthesis using Fraction Based Waveform Concatenation and Optimal Coupling Smoothing Technique." International Journal of Recent Technology and Engineering 9, no. 1 (2020): 1764–69. http://dx.doi.org/10.35940/ijrte.a2530.059120.

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Text to Speech System is a Speech Synthesis application that converts a text to speech. The current project focuses on developing a TTS System for the Tamil Language with the Synthesis Technique as Unit Selection Synthesis. Letter Level Segmentation of an input text helps in the reduction of corpus size compared to Syllable Level Segmentation. The segmented units are retrieved with respect to Unicode values, concatenated and the synthesized speech is produced. Intelligibility and Naturalness of the spoken word can be improved using the Smoothing Techniques. Optimal Coupling Smoothing Technique

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Zheng, Xin-Yang, Jin Lin, Yu-Huai Li, Min-Yan Wang, Sheng-Kai Liao, and Cheng-Zhi Peng. "Encoding control system for twin-field quantum key distribution." AIP Advances 14, no. 6 (2024). http://dx.doi.org/10.1063/5.0206186.

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The Twin-Field Quantum Key Distribution (TF-QKD) protocol has the potential to realize secure key distribution over extremely long distances, which is an important technique for realizing a global quantum network. Compared to the conventional BB84 protocol, practical TF-QKD and its variant protocols require an accurate phase modulation to at least 16 different values with randomized encoding. In this work, we developed an encoding control system for TF-QKD. Optical pulses with five different intensities and 16 different phases can be modulated with a clock frequency of 100 MHz with a field pro

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Books on the topic "Waveform Concatenation Technique"

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Dutoit, Thierry, and Yannis Stylianou. Text-to-Speech Synthesis. Edited by Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0017.

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This article gives an introduction to state-of-the-art text-to-speech (TTS) synthesis systems, showing both the natural language processing and the digital signal processing problems involved. Text-to-speech (TTS) synthesis is the art of designing talking machines. The article begins with brief user-oriented description of a general TTS system and comments on its commercial applications. It then gives a functional diagram of a modern TTS system, highlighting its components. It describes its morphosyntactic module. Furthermore, it examines why sentence-level phonetization cannot be achieved by

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Book chapters on the topic "Waveform Concatenation Technique"

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Panda, Soumya Priyadarsini, and Ajit Kumar Nayak. "Spectral Smoothening Based Waveform Concatenation Technique for Speech Quality Enhancement in Text-to-Speech Systems." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1081-6_36.

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Conference papers on the topic "Waveform Concatenation Technique"

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Panda, Soumya Priyadarsini, and Ajit Kumar Nayak. "Vowel onset point based waveform concatenation technique for intelligible speech synthesis." In 2017 International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2017. http://dx.doi.org/10.1109/iccmc.2017.8282542.

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Panda, Soumya Priyadarsini, and Ajit Kumar Nayak. "Integration of Fuzzy If-Then Rule with Waveform Concatenation Technique for Text-to-Speech Synthesis in Odia." In 2014 International Conference on Information Technology (ICIT). IEEE, 2014. http://dx.doi.org/10.1109/icit.2014.37.

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