{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T15:07:18Z","timestamp":1788361638593,"version":"build-2803163510"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T00:00:00Z","timestamp":1599696000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T00:00:00Z","timestamp":1599696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100009567","name":"Budapest University of Technology and Economics","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100009567","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This article focuses on developing a system for high-quality synthesized and converted speech by addressing three fundamental principles. Although the noise-like component in the state-of-the-art parametric vocoders (for example, STRAIGHT) is often not accurate enough, a novel analytical approach for modeling unvoiced excitations using a temporal envelope is proposed. Discrete All Pole, Frequency Domain Linear Prediction, Low Pass Filter, and True envelopes are firstly studied and applied to the noise excitation signal in our continuous vocoder. Second, we build a deep learning model based text\u2013to\u2013speech (TTS) which converts written text into human-like speech with a feed-forward and several sequence-to-sequence models (long short-term memory, gated recurrent unit, and hybrid model). Third, a new voice conversion system is proposed using a continuous fundamental frequency to provide accurate time-aligned voiced segments. The results have been evaluated in terms of objective measures and subjective listening tests. Experimental results showed that the proposed models achieved the highest speaker similarity and better quality compared with the other conventional methods.<\/jats:p>","DOI":"10.1007\/s11042-020-09783-9","type":"journal-article","created":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T22:02:57Z","timestamp":1599775377000},"page":"1969-1994","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Noise and acoustic modeling with waveform generator in text-to-speech and neutral speech conversion"],"prefix":"10.1007","volume":"80","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3094-6916","authenticated-orcid":false,"given":"Mohammed Salah","family":"Al-Radhi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tam\u00e1s G\u00e1bor","family":"Csap\u00f3","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G\u00e9za","family":"N\u00e9meth","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,9,10]]},"reference":[{"key":"9783_CR1","doi-asserted-by":"publisher","unstructured":"Al-Radhi MS, Csap\u00f3 TG, N\u00e9meth G (2017) Deep Recurrent Neural Networks in Speech Synthesis Using a Continuous Vocoder. In: proceedings of the speech and computer (SPECOM), Hatfield, UK, Springer, 2017, p 282\u2013291. https:\/\/doi.org\/10.1007\/978-3-319-66429-3_27","DOI":"10.1007\/978-3-319-66429-3_27"},{"key":"9783_CR2","doi-asserted-by":"publisher","unstructured":"Al-Radhi MS, Csap\u00f3 TG, N\u00e9meth G (2017) Time-domain envelope modulating the noise component of excitation in a continuous residual-based vocoder for statistical parametric speech synthesis. In: proceedings of the Interspeech, Stockholm, p 434-438. https:\/\/doi.org\/10.21437\/Interspeech.2017-678","DOI":"10.21437\/Interspeech.2017-678"},{"key":"9783_CR3","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1109\/ASRU.2003.1318451","volume-title":"Frequency-domain linear prediction for temporal features","author":"M Athineos","year":"2003","unstructured":"Athineos M, ELLIS D (2003) Frequency-domain linear prediction for temporal features. Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding, USA, In, pp 261\u2013266. https:\/\/doi.org\/10.1109\/ASRU.2003.1318451"},{"issue":"2","key":"9783_CR4","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1109\/72.279181","volume":"5","author":"Y Bengio","year":"1994","unstructured":"Bengio Y, Simard P, Frasconi P (1994) Learning long-term dependencies with gradient descent is difficult. IEEE Trans Neural Netw 5(2):157\u2013166. https:\/\/doi.org\/10.1109\/72.279181","journal-title":"IEEE Trans Neural Netw"},{"key":"9783_CR5","doi-asserted-by":"publisher","unstructured":"Cabral JP, Berndsen JC (2013) Towards a better representation of the envelope modulation of aspiration noise. In: proceedings of the advances in nonlinear speech processing (NOLISP), Berlin Heidelberg, p 67-74. https:\/\/doi.org\/10.1007\/978-3-642-38847-7_9","DOI":"10.1007\/978-3-642-38847-7_9"},{"key":"9783_CR6","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/978-3-319-25789-1_4","volume-title":"Proceedings of the international conference on statistical language and speech processing","author":"TG Csap\u00f3","year":"2015","unstructured":"Csap\u00f3 TG, N\u00e9meth G, Cernak M (2015) Residual-based excitation with continuous F0 modeling in HMM-based speech synthesis. In: Proceedings of the international conference on statistical language and speech processing. Budapest, Hungary, pp 27\u201338. https:\/\/doi.org\/10.1007\/978-3-319-25789-1_4"},{"issue":"1","key":"9783_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13636-014-0038-1","volume":"38","author":"G Degottex","year":"2014","unstructured":"Degottex G, Erro D (2014) A uniform phase representation for the harmonic model in speech synthesis applications. EURASIP Journal of Audio, Speech, Music Processing 38(1):1\u201316. https:\/\/doi.org\/10.1186\/s13636-014-0038-1","journal-title":"EURASIP Journal of Audio, Speech, Music Processing"},{"key":"9783_CR8","doi-asserted-by":"crossref","unstructured":"Degottex G, Lanchantin P, Gales M (2016) A pulse model in log-domain for a uniform synthesizer. In: proceedings of the international speech communication association speech synthesis workshop (ISCA SSW9), California, p 230\u2013236","DOI":"10.21437\/SSW.2016-35"},{"key":"9783_CR9","doi-asserted-by":"publisher","unstructured":"Desai S, Raghavendra EV, Yegnanarayana B, Black AW, Prahallad K (2009) Voice conversion using artificial neural networks. In: proceedings of the international conference on acoustics, speech, and signal processing (ICASSP), Taiwan, p 3893-3896. https:\/\/doi.org\/10.1109\/ICASSP.2009.4960478","DOI":"10.1109\/ICASSP.2009.4960478"},{"key":"9783_CR10","doi-asserted-by":"publisher","first-page":"9871","DOI":"10.1007\/s11042-014-2156-2","volume":"74","author":"C Ding","year":"2015","unstructured":"Ding C, Xie L, Zhu P (2015) Head motion synthesis from speech using deep neural networks. Multimed Tools Appl 74:9871\u20139888. https:\/\/doi.org\/10.1007\/s11042-014-2156-2","journal-title":"Multimed Tools Appl"},{"issue":"3","key":"9783_CR11","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1109\/TASL.2011.2169787","volume":"20","author":"T Drugman","year":"2012","unstructured":"Drugman T, Dutoit T (2012) The deterministic plus stochastic model of the residual signal and its applications. IEEE Trans Audio Speech Lang Process 20(3):968\u2013981. https:\/\/doi.org\/10.1109\/TASL.2011.2169787","journal-title":"IEEE Trans Audio Speech Lang Process"},{"issue":"10","key":"9783_CR12","doi-asserted-by":"publisher","first-page":"1230","DOI":"10.1109\/LSP.2014.2332186","volume":"21","author":"T Drugman","year":"2014","unstructured":"Drugman T, Stylianou Y (2014) Maximum voiced frequency estimation: exploiting amplitude and phase spectra. IEEE Signal Processing Letters 21(10):1230\u20131234. https:\/\/doi.org\/10.1109\/LSP.2014.2332186","journal-title":"IEEE Signal Processing Letters"},{"issue":"1","key":"9783_CR13","doi-asserted-by":"publisher","first-page":"585","DOI":"10.1121\/1.413112","volume":"97","author":"R Drullman","year":"1995","unstructured":"Drullman R (1995) Temporal envelope and fine structure cues for speech intelligibility. J Acoust Soc Am 97(1):585\u2013591. https:\/\/doi.org\/10.1121\/1.413112","journal-title":"J Acoust Soc Am"},{"issue":"2","key":"9783_CR14","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1109\/78.80824","volume":"39","author":"A El-Jaroudi","year":"1991","unstructured":"El-Jaroudi A, Makhoul J (1991) Discrete all-pole modeling. IEEE Trans Signal Process 39(2):411\u2013423. https:\/\/doi.org\/10.1109\/78.80824","journal-title":"IEEE Trans Signal Process"},{"key":"9783_CR15","doi-asserted-by":"publisher","unstructured":"Espic F, Botinhao CV, King S (2017) Direct Modelling of magnitude and phase spectra for statistical parametric speech synthesis. In: proceedings of the Interspeech, Stockholm, p 1383-1387. https:\/\/doi.org\/10.21437\/Interspeech.2017-1647","DOI":"10.21437\/Interspeech.2017-1647"},{"key":"9783_CR16","doi-asserted-by":"publisher","unstructured":"Espic F, Valentini-Botinhao C, King S (2017) Direct Modelling of magnitude and phase spectra for statistical parametric speech synthesis. In: proceedings of the Interspeech, Stockholm, p 1383-1387. https:\/\/doi.org\/10.21437\/Interspeech.2017-1647","DOI":"10.21437\/Interspeech.2017-1647"},{"key":"9783_CR17","volume-title":"Soong FK (2014) TTS synthesis with bidirectional LSTM based recurrent neural networks","author":"Y Fan","year":"1964","unstructured":"Fan Y, Qian Y, Xie F (1964-1968) Soong FK (2014) TTS synthesis with bidirectional LSTM based recurrent neural networks. In, Proceedings of the Interspeech, Singapore, p"},{"key":"9783_CR18","doi-asserted-by":"publisher","unstructured":"Fisher NI (1995) Statistical analysis of circular data. Cambridge University, UK. https:\/\/doi.org\/10.1017\/CBO9780511564345","DOI":"10.1017\/CBO9780511564345"},{"issue":"1","key":"9783_CR19","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1109\/LSP.2012.2231675","volume":"20","author":"PN Garner","year":"2013","unstructured":"Garner PN, Cernak M, Motlicek P (2013) A simple continuous pitch estimation algorithm. IEEE Signal Processing Letters 20(1):102\u2013105. https:\/\/doi.org\/10.1109\/LSP.2012.2231675","journal-title":"IEEE Signal Processing Letters"},{"key":"9783_CR20","unstructured":"Herre J, Johnston JD (1996) Enhancing the performance of perceptual audio coders by using temporal noise shaping (TNS). In: proceedings of the 101st audio engineering society convention, Los Angeles."},{"issue":"8","key":"9783_CR21","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780. https:\/\/doi.org\/10.1162\/neco.1997.9.8.1735","journal-title":"Neural Comput"},{"issue":"2","key":"9783_CR22","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1002\/ecja.4400660203","volume":"66","author":"S Imai","year":"1983","unstructured":"Imai S, Sumita K, Furuichi C (1983) Mel log Spectrum approximation (MLSA) filter for speech synthesis. Electronics and Communications in Japan (Part I: Communications) 66(2):10\u201318. https:\/\/doi.org\/10.1002\/ecja.4400660203","journal-title":"Electronics and Communications in Japan (Part I: Communications)"},{"key":"9783_CR23","unstructured":"ITU-R BS.1534 (2001) Method for the subjective assessment of intermediate audio quality."},{"issue":"5","key":"9783_CR24","doi-asserted-by":"publisher","first-page":"1071","DOI":"10.1109\/TASL.2010.2076805","volume":"19","author":"Y Kai","year":"2011","unstructured":"Kai Y, Steve Y (2011) Continuous F0 modeling for HMM based statistical parametric speech synthesis. IEEE Trans Audio Speech Lang Process 19(5):1071\u20131079. https:\/\/doi.org\/10.1109\/TASL.2010.2076805","journal-title":"IEEE Trans Audio Speech Lang Process"},{"key":"9783_CR25","unstructured":"Kai Y, Blaise T, Steve Y (2010) From discontinuous to continuous F0 Modelling in HMM-based speech synthesis. In: proceedings of the international speech communication association speech synthesis workshop (ISCA SSW7), Kyoto, p 94\u201399"},{"key":"9783_CR26","doi-asserted-by":"publisher","unstructured":"Kaneko T, Kameoka H, Hiramatsu K, Kashino K (2017) Sequence-to-sequence voice conversion with similarity metric learned using generative adversarial networks. In: proceedings of the Interspeech, Stockholm, p 1283-1287. https:\/\/doi.org\/10.21437\/Interspeech.2017-970","DOI":"10.21437\/Interspeech.2017-970"},{"issue":"3\u20134","key":"9783_CR27","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/S0167-6393(98)00085-5","volume":"27","author":"H Kawahara","year":"1999","unstructured":"Kawahara H, Katsuse IM, Cheveigne AD (1999) Restructuring speech representations using a pitch-adaptive time\u2013frequency smoothing and an instantaneous-frequency-based F0 extraction. Speech Comm 27(3\u20134):187\u2013207. https:\/\/doi.org\/10.1016\/S0167-6393(98)00085-5","journal-title":"Speech Comm"},{"key":"9783_CR28","doi-asserted-by":"publisher","unstructured":"Kobayashi K, Toda T (2018) Sprocket: open-source voice conversion software. In: proceedings of the odyssey: the speaker and language recognition, p 203-210. https:\/\/doi.org\/10.21437\/Odyssey.2018-29","DOI":"10.21437\/Odyssey.2018-29"},{"key":"9783_CR29","unstructured":"Kominek J, Black AW (2003) CMU ARCTIC databases for speech synthesis. Language Technologies Institute [Online] Available: http:\/\/festvox.org\/cmu_arctic\/"},{"key":"9783_CR30","doi-asserted-by":"publisher","unstructured":"Kotani G, Saito D, Minematsu N (2017) Voice conversion based on deep neural networks for time-variant linear transformations. In: proceedings of the Asia-Pacific signal and information processing association annual summit and conference (APSIPA ASC), Kuala Lumpur, p 1259-1262. https:\/\/doi.org\/10.1109\/APSIPA.2017.8282216","DOI":"10.1109\/APSIPA.2017.8282216"},{"key":"9783_CR31","doi-asserted-by":"publisher","first-page":"29847","DOI":"10.1007\/s11042-018-5856-1","volume":"77","author":"X Li","year":"2018","unstructured":"Li X, Yuan A, Lu X (2018) Multi-modal gated recurrent units for image description. Multimed Tools Appl 77:29847\u201329869. https:\/\/doi.org\/10.1007\/s11042-018-5856-1","journal-title":"Multimed Tools Appl"},{"issue":"5","key":"9783_CR32","doi-asserted-by":"publisher","first-page":"3387","DOI":"10.1121\/1.3097493","volume":"125","author":"J Ma","year":"2009","unstructured":"Ma J, Hu Y, Loizou PC (2009) Objective measures for predicting speech intelligibility in noisy conditions based on new band-importance functions. Acoustical Society of America 125(5):3387\u20133405. https:\/\/doi.org\/10.1121\/1.3097493","journal-title":"Acoustical Society of America"},{"key":"9783_CR33","volume-title":"Buchholz S (2011) multipulse sequences for residual signal modeling","author":"R Maia","year":"1833","unstructured":"Maia R, Zen H, Knill K, Gales M (1833\u20131836) Buchholz S (2011) multipulse sequences for residual signal modeling. In, Proceedings of the Interspeech, p"},{"key":"9783_CR34","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.specom.2014.09.003","volume":"67","author":"M Morise","year":"2015","unstructured":"Morise M (2015) CHEAPTRICK, a spectral envelope estimator for high-quality speech synthesis. Speech Comm 67:1\u20137. https:\/\/doi.org\/10.1016\/j.specom.2014.09.003","journal-title":"Speech Comm"},{"issue":"2","key":"9783_CR35","first-page":"109","volume":"J93-D","author":"M Morise","year":"2010","unstructured":"Morise M, Kawahara H, Nishiura T (2010) Rapid f0 estimation for high SNR speech based on fundamental component extraction. IEICE transactions information systems J93-D(2):109\u2013117","journal-title":"IEICE transactions information systems"},{"issue":"7","key":"9783_CR36","doi-asserted-by":"publisher","first-page":"1877","DOI":"10.1587\/transinf.2015EDP7457","volume":"E99-D","author":"M Morise","year":"2016","unstructured":"Morise M, Yokomori F, Ozawa K (2016) WORLD: a vocoder-based high-quality speech synthesis system for real-time applications. IEICE Trans Inf Syst E99-D(7):1877\u20131884. https:\/\/doi.org\/10.1587\/transinf.2015EDP7457","journal-title":"IEICE Trans Inf Syst"},{"issue":"1","key":"9783_CR37","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-014-0007-7","volume":"2","author":"M Najafabadi","year":"2015","unstructured":"Najafabadi M, Villanustre F, Khoshgoftaar T, Seliya N, Wald R, Muharemagic E (2015) Deep learning applications and challenges in big data analytics. Journal of Big Data 2(1):1\u201321. https:\/\/doi.org\/10.1186\/s40537-014-0007-7","journal-title":"Journal of Big Data"},{"issue":"1","key":"9783_CR38","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1016\/j.specom.2011.07.007","volume":"54","author":"K Nakamura","year":"2012","unstructured":"Nakamura K, Toda T, Saruwatari H, Shikano K (2012) Speaking-aid systems using GMM-based voice conversion for electrolaryngeal speech. Speech Comm 54(1):134\u2013146. https:\/\/doi.org\/10.1016\/j.specom.2011.07.007","journal-title":"Speech Comm"},{"key":"9783_CR39","first-page":"369","volume-title":"Proceedings of the Interspeech","author":"T Nakashika","year":"2013","unstructured":"Nakashika T, Takashima R, Takiguchi T, Ariki Y (2013) Voice conversion in high-order eigen space using deep belief nets. In: Proceedings of the Interspeech. Lyon, France, pp 369\u2013372"},{"issue":"6","key":"9783_CR40","doi-asserted-by":"publisher","first-page":"1403","DOI":"10.1587\/transinf.E97.D.1403","volume":"97","author":"T Nakashika","year":"2014","unstructured":"Nakashika T, Takiguchi T, Ariki Y (2014) Voice conversion based on speaker-dependent restricted boltzmann machines. IEICE Trans Inf Syst 97(6):1403\u20131410","journal-title":"IEICE Trans Inf Syst"},{"issue":"2","key":"9783_CR41","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1109\/TASSP.1984.1164320","volume":"32","author":"H Ney","year":"1984","unstructured":"Ney H (1984) The use of a one-state dynamic programming algorithm for connected word recognition. IEEE Trans Acoust Speech Signal Process 32(2):263\u2013271. https:\/\/doi.org\/10.1109\/TASSP.1984.1164320","journal-title":"IEEE Trans Acoust Speech Signal Process"},{"key":"9783_CR42","doi-asserted-by":"publisher","unstructured":"Pantazis Y, Stylianou Y (2008) Improving the modeling of the noise part in the harmonic plus noise model of speech. In: proceedings of the international conference on acoustics, speech, and signal processing (ICASSP), Nevada, p 4609-4612. https:\/\/doi.org\/10.1109\/ICASSP.2008.4518683","DOI":"10.1109\/ICASSP.2008.4518683"},{"key":"9783_CR43","unstructured":"Qiong H, Richmond K, Yamagishi J, Latorre J (2013) An experimental comparison of multiple vocoder types, in: proceedings of the international speech communication association speech synthesis workshop (ISCA SSW8), Barcelona, p 155\u2013160"},{"key":"9783_CR44","volume-title":"Objective measures of speech quality","author":"S Quackenbush","year":"1988","unstructured":"Quackenbush S, Barnwell T, Clements M (1988) Objective measures of speech quality. Prentice-Hall, Englewood Cliffs, NJ"},{"key":"9783_CR45","first-page":"30","volume-title":"Efficient spectral envelope estimation and its application to pitch shifting and envelope preservation","author":"A Robel","year":"2005","unstructured":"Robel A, Rodet X (2005) Efficient spectral envelope estimation and its application to pitch shifting and envelope preservation. Proceedings of the International Conference on Digital Audio Effects, Spain, In, pp 30\u201335"},{"issue":"1","key":"9783_CR46","doi-asserted-by":"publisher","first-page":"1343","DOI":"10.1016\/j.patrec.2006.11.021","volume":"28","author":"A Robel","year":"2007","unstructured":"Robel A, Villavicencio F, Rodet X (2007) On cepstral and all-pole based spectral envelope modeling with unknown model order. Pattern Recogn Lett 28(1):1343\u20131350. https:\/\/doi.org\/10.1016\/j.patrec.2006.11.021","journal-title":"Pattern Recogn Lett"},{"key":"9783_CR47","doi-asserted-by":"publisher","unstructured":"Saito Y, Ijima Y, Nishida K, Takamichi S (2018) Non-parallel voice conversion using variational autoencoders conditioned by phonetic posteriorgrams and d-vectors. In: proceedings of the international conference on acoustics, speech, and signal processing (ICASSP), Canada, p 5274-5278. https:\/\/doi.org\/10.1109\/ICASSP.2018.8461384","DOI":"10.1109\/ICASSP.2018.8461384"},{"issue":"1","key":"9783_CR48","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1109\/TASSP.1978.1163055","volume":"26","author":"H Sakoe","year":"1978","unstructured":"Sakoe H, Chiba S (1978) Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions Acoustic Speech Signal Processing 26(1):43\u201349. https:\/\/doi.org\/10.1109\/TASSP.1978.1163055","journal-title":"IEEE Transactions Acoustic Speech Signal Processing"},{"key":"9783_CR49","unstructured":"Schloss A (1985) On the automatic transcription of percussive music - from acoustic signal to high-level analysis, Ph.D. thesis, Stanford University."},{"issue":"11","key":"9783_CR50","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.1109\/78.650093","volume":"45","author":"M Schuster","year":"1997","unstructured":"Schuster M, Paliwal K (1997) Bidirectional recurrent neural networks. IEEE Trans Signal Process 45(11):2673\u20132681. https:\/\/doi.org\/10.1109\/78.650093","journal-title":"IEEE Trans Signal Process"},{"issue":"1","key":"9783_CR51","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/89.890068","volume":"9","author":"Y Stylianou","year":"2001","unstructured":"Stylianou Y (2001) Applying the harmonic plus noise model in concatenative speech synthesis. IEEE Transactions Audio, Speech, Language Processing 9(1):21\u201329. https:\/\/doi.org\/10.1109\/89.890068","journal-title":"IEEE Transactions Audio, Speech, Language Processing"},{"issue":"2","key":"9783_CR52","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1109\/89.661472","volume":"6","author":"Y Stylianou","year":"1998","unstructured":"Stylianou Y, Cappe O, Moulines E (1998) Continuous probabilistic transform for voice conversion. IEEE Transactions Speech and Audio Processing 6(2):131\u2013142. https:\/\/doi.org\/10.1109\/89.661472","journal-title":"IEEE Transactions Speech and Audio Processing"},{"key":"9783_CR53","doi-asserted-by":"publisher","unstructured":"Sun L, Kang S, Li K, Meng H (2015) Voice conversion using deep bidirectional long short-term memory based recurrent neural networks. In: proceedings of the international conference on acoustics, speech, and signal processing (ICASSP), Brisbane, Australia, 2015, pp. 4869-4873. https:\/\/doi.org\/10.1109\/ICASSP.2015.7178896","DOI":"10.1109\/ICASSP.2015.7178896"},{"issue":"8","key":"9783_CR54","doi-asserted-by":"publisher","first-page":"2222","DOI":"10.1109\/TASL.2007.907344","volume":"15","author":"T Toda","year":"2007","unstructured":"Toda T, Black AW, Tokuda K (2007) Voice conversion based on maximum-likelihood estimation of spectral parameter trajectory. IEEE Trans Audio Speech Lang Process 15(8):2222\u20132235. https:\/\/doi.org\/10.1109\/TASL.2007.907344","journal-title":"IEEE Trans Audio Speech Lang Process"},{"issue":"9","key":"9783_CR55","doi-asserted-by":"publisher","first-page":"2505","DOI":"10.1109\/TASL.2012.2205241","volume":"20","author":"T Toda","year":"2012","unstructured":"Toda T, Nakagiri M, Shikano K (2012) Statistical voice conversion techniques for body-conducted unvoiced speech enhancement. IEEE Trans Audio Speech Lang Process 20(9):2505\u20132517. https:\/\/doi.org\/10.1109\/TASL.2012.2205241","journal-title":"IEEE Trans Audio Speech Lang Process"},{"key":"9783_CR56","doi-asserted-by":"crossref","unstructured":"Tokuda K, Kobayashi T, Masuko T, Imai S (1994) Mel-generalized cepstral analysis - a unified approach to speech spectral estimation. In: proceedings of the international conference on spoken language processing (ICSLP), Yokohama, p 1043\u20131046.","DOI":"10.21437\/ICSLP.1994-275"},{"issue":"3","key":"9783_CR57","first-page":"455","volume":"E85-D","author":"K Tokuda","year":"2002","unstructured":"Tokuda K, Mausko T, Miyazaki N, Kobayashi T (2002) Multi-space probability distribution HMM. IEICE Trans Inf Syst E85-D(3):455\u2013464","journal-title":"IEICE Trans Inf Syst"},{"key":"9783_CR58","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1109\/ICASSP.2006.1660159","volume-title":"Proceedings of the international conference on acoustics, speech, and signal processing (ICASSP)","author":"F Villavicencio","year":"2006","unstructured":"Villavicencio F, Robel A, Rodet X (2006) Improving LPC spectral envelope extraction of voiced speech by true-envelope estimation. In: Proceedings of the international conference on acoustics, speech, and signal processing (ICASSP). Toulouse, France, pp 869\u2013872. https:\/\/doi.org\/10.1109\/ICASSP.2006.1660159"},{"key":"9783_CR59","doi-asserted-by":"publisher","first-page":"4460","DOI":"10.1109\/ICASSP.2015.7178814","volume-title":"Proceedings of the international conference on acoustics, speech, and signal processing (ICASSP)","author":"Z Wu","year":"2015","unstructured":"Wu Z, Botinhao CV, Watts O, King S (2015) Deep neural networks employing multi-task learning and stacked bottleneck features for speech synthesis. In: Proceedings of the international conference on acoustics, speech, and signal processing (ICASSP). Brisbane, Australia, pp 4460\u20134464. https:\/\/doi.org\/10.1109\/ICASSP.2015.7178814"},{"key":"9783_CR60","doi-asserted-by":"publisher","first-page":"9943","DOI":"10.1007\/s11042-014-2180-2","volume":"74","author":"Z Wu","year":"2015","unstructured":"Wu Z, Chng ES, Li H (2015) Exemplar-based voice conversion using joint nonnegative matrix factorization. Multimed Tools Appl 74:9943\u20139958. https:\/\/doi.org\/10.1007\/s11042-014-2180-2","journal-title":"Multimed Tools Appl"},{"key":"9783_CR61","doi-asserted-by":"publisher","unstructured":"Zen H, Senior A (2014) Deep mixture density networks for acoustic modeling in statistical parametric speech synthesis. In: proceedings of the international conference on acoustics, speech, and signal processing (ICASSP), Florence, p 3844-3848. https:\/\/doi.org\/10.1109\/ICASSP.2014.6854321","DOI":"10.1109\/ICASSP.2014.6854321"},{"issue":"11","key":"9783_CR62","doi-asserted-by":"publisher","first-page":"1039","DOI":"10.1016\/j.specom.2009.04.004","volume":"51","author":"H Zen","year":"2009","unstructured":"Zen H, Tokuda K, Black AW (2009) Statistical parametric speech synthesis. Speech Comm 51(11):1039\u20131064. https:\/\/doi.org\/10.1016\/j.specom.2009.04.004","journal-title":"Speech Comm"},{"key":"9783_CR63","doi-asserted-by":"publisher","unstructured":"Zen H, Senior A, Schuster M (2013) Statistical parametric speech synthesis using deep neural network. In: proceedings of the international conference on acoustics, speech, and signal processing (ICASSP), Vancouver, p 7962\u20137966. https:\/\/doi.org\/10.1109\/ICASSP.2013.6639215","DOI":"10.1109\/ICASSP.2013.6639215"},{"key":"9783_CR64","doi-asserted-by":"publisher","unstructured":"Zhizheng W, Watts O, King S (2016) Merlin: an open source neural network speech synthesis system. In: proceedings of the international speech communication association speech synthesis workshop (ISCA SSW9), Sunnyvale, CA, USA. https:\/\/doi.org\/10.21437\/SSW.2016-33","DOI":"10.21437\/SSW.2016-33"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09783-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-09783-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09783-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,17]],"date-time":"2022-11-17T20:32:43Z","timestamp":1668717163000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-09783-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,10]]},"references-count":64,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["9783"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09783-9","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,10]]},"assertion":[{"value":"14 April 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 July 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 August 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 September 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}