“Waveglow: a flow-based generative network for speech synthesis,”

Adam: A Method for Stochastic Optimization

Kingma, D. P., & Ba, J. (2014) · arXiv · doi:10.48550/arxiv.1412.6980 · Cited by 98,946

WaveNet: a generative model for raw audio

Oord, A. V. D., Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., Kalchbrenner, N., Senior, A., & Kavukcuoglu, K. (2016) · arXiv · doi:10.48550/arxiv.1609.03499 · Cited by 4,911

Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions

Shen, J., Pang, R., Weiss, R. J., Schuster, M., Jaitly, N., Yang, Z., Chen, Z., Zhang, Y., Wang, Y., Skerrv-Ryan, R., et al. (2018) · 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp.2018.8461368 · Cited by 2,791

Variational Inference with Normalizing FlowsPreprint

Rezende, D. J., & Mohamed, S. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1505.05770 · Cited by 2,583

Signal estimation from modified short-time Fourier transform

Griffin, D. W., & Lim, J. S. (1984) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/tassp.1984.1164317 · Cited by 2,085

Density estimation using Real NVP

Dinh, L., Sohl-Dickstein, J., & Bengio, S. (2016) · arXiv · Cited by 2,067

Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural NetworksPreprint

Salimans, T., & Kingma, D. P. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1602.07868 · Cited by 1,551

NICE: Non-linear Independent Components Estimation

Dinh, L., Krueger, D., & Bengio, Y. (2014) · arXiv · doi:10.48550/arxiv.1410.8516 · Cited by 1,493

Improving Variational Inference with Inverse Autoregressive FlowPreprint

Kingma, D., Salimans, T., Józefowicz, R., Chen, X., Sutskever, I., & Welling, M. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1606.04934 · Cited by 1,168

Image transformer

Parmar, N., Vaswani, A., Uszkoreit, J., Kaiser, Ł., Shazeer, N., Ku, A., & Tran, D. (2018) · arXiv · doi:10.48550/arxiv.1802.05751 · Cited by 1,085

Karaoker: Alignment-free singing voice synthesis with speech training data

Kakoulidis, P., Ellinas, N., Vamvoukakis, G., Μαρκόπουλος, Κ., Sung, J. S., Jho, G., Tsiakoulis, P., & Chalamandaris, A. (2022) · Interspeech (USB) · doi:10.21437/interspeech.2022-10446 · Cited by 3

TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed

Du, S., Luo, Y., Chen, W., Xu, J., & Zeng, D. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01224 · Cited by 3

Foreign Accent Conversion using Concentrated Attention

Zang, X., Xie, F., & Weng, F. (2022) · IEEE International Conference on Knowledge Graph (ICKG) · doi:10.1109/ickg55886.2022.00056 · Cited by 3

NIX-TTS: Lightweight and End-to-End Text-to-Speech Via Module-Wise Distillation

Chevi, R., Prasojo, R. E., Aji, A. F., Tjandra, A., & Sakti, S. (2023) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt54892.2023.10023322 · Cited by 3

Source-Filter-Based Generative Adversarial Neural Vocoder for High Fidelity Speech Synthesis

Lu, Y.-X., Ai, Y., & Ling, Z.-H. (2023) · Communications in computer and information science · doi:10.1007/978-981-99-2401-1_6 · Cited by 3

NAS-FM: Neural Architecture Search for Tunable and Interpretable Sound Synthesis Based on Frequency Modulation

Ye, Z., Xue, W., Tan, X., Liu, Q., & Guo, Y. (2023) · International Joint Conference on Artificial Intelligence · doi:10.24963/ijcai.2023/651 · Cited by 3

Local Style Tokens: Fine-Grained Prosodic Representations For TTS Expressive Control

Lenglet, M., Perrotin, O., & Bailly, G. (2023) · ISCA Speech Synthesis Workshop (SSW) · doi:10.21437/ssw.2023-19 · Cited by 5

Research on Speech Synthesis Based on Mixture Alignment Mechanism

Deng, Y., Wu, N., Qiu, C., Chen, Y., & Gao, X. (2023) · Sensors · doi:10.3390/s23167283 · Cited by 3

The GIPSA-Lab Text-To-Speech System for the Blizzard Challenge 2023

Lenglet, M., Perrotin, O., & Bailly, G. (2023) · doi:10.21437/blizzard.2023-3 · Cited by 3

Rules for Expectation: Learning to Generate Rules via Social Environment Modeling

Pu, J., Duan, H., Zhao, J., & Long, Y. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3334526 · Cited by 3

A Lightweight and Efficient Model for Audio Anti-Spoofing

Ma, Q., Zhong, J., Yang, Y., Liu, W., Gao, Y., & Ng, W. W. Y. (2023) · ACM International Conference on Multimedia in Asia (MMAsia) · doi:10.1145/3595916.3626403 · Cited by 3

Invertible Voice Conversion with Parallel Data

Cai, Z., & Li, M. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10447701 · Cited by 3

THInImg: Cross-modal Steganography for Presenting Talking Heads in Images

Zhao, L., Li, H., Ning, X., & Jiang, X. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00546 · Cited by 3

GRU-SVM Model for Synthetic Speech Detection

Huang, T., Wang, H., Chen, Y., & He, P. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-43575-2_9 · Cited by 3

Speaker-Adaptive Neural Vocoders for Parametric Speech Synthesis Systems

Song, E., Kim, J., Byun, K., & Kang, H.-G. (2020) · IEEE International Workshop on Multimedia Signal Processing (MMSP) · doi:10.1109/mmsp48831.2020.9287168 · Cited by 3

Comparison of CNN-based Speech Dereverberation using Neural Vocoder

Chun, C., Jeon, K. M., Leem, C., Lee, B., & Choi, W. (2021) · International Conference on Artificial Intelligence in Information and Communication (ICAIIC) · doi:10.1109/icaiic51459.2021.9415259 · Cited by 3

Designing and Deploying an Interaction Modality for Articulatory-Based Audiovisual Speech Synthesis

Almeida, N., Cunha, D., Silva, S., & Teixeira, A. J. S. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-87802-3_4 · Cited by 3

Multi-Sample Subband Wavernn Via Multivariate Gaussian

Kanagawa, H., & Ijima, Y. (2022) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp43922.2022.9747898 · Cited by 3

Improving Fastspeech TTS with Efficient Self-Attention and Compact Feed-Forward Network

Xiao, Y., Wang, X., He, L., & Soong, F. K. (2022) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp43922.2022.9746408 · Cited by 3

SATTS: Speaker Attractor Text to Speech, Learning to Speak by Learning to Separate

Goswami, N., & Harada, T. (2022) · Interspeech (USB) · doi:10.21437/interspeech.2022-133 · Cited by 3

Curating Generative Raw Audio Music with D.O.M.E.

Carr, C., & Zukowski, Z. (2019) · IUI Workshops · Cited by 3

The first FOSD-tacotron-2-based text-to-speech application for Vietnamese

Tran, D. C. (2021) · Bulletin of Electrical Engineering and Informatics · doi:10.11591/eei.v10i2.2539 · Cited by 3

Emotional Vietnamese Speech Synthesis Using Style-Transfer Learning

Xuan, T. L., Le, A. T., & Nguyen, Q. H. (2022) · Computer Systems Science and Engineering · doi:10.32604/csse.2023.026234 · Cited by 3

PUFFIN: Pitch-Synchronous Neural Waveform Generation for Fullband Speech on Modest Devices

Watts, O., Wihlborg, L., & Valentini-Botinhao, C. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10094729 · Cited by 3

Axial Residual Networks for CycleGAN-based Voice ConversionPreprint

You, J., Nam, G., Kim, D.-H., & Chae, G. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2102.08075 · Cited by 3

Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with ExplainabilityPreprint

Ghosh, A., Honoré, A., Liu, D., Henter, G. E., & Chatterjee, S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.00730 · Cited by 3

Uncertainty quantification for ptychography using normalizing flowsPreprint

Dasgupta, A., & Di, Z. W. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.00745 · Cited by 3

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts

(2022) · doi:10.18653/v1/2022.emnlp-tutorials · Cited by 3

Anonymizing Speech : Evaluating and Designing Speaker Anonymization Techniques

Champion, P. (2023) · theses.fr (ABES) · doi:10.70675/067b0cedz8667z43b8zb7c0zf7fd22daf495 · Cited by 4

Adaptation of Tacotron2-based Text-To-Speech for Articulatory-to-Acoustic Mapping using Ultrasound Tongue Imaging

Zainkó, C., Tóth, L., Shandiz, A. H., Gosztolya, G., Markó, A., Németh, G., & Csapó, T. G. (2021) · ISCA Speech Synthesis Workshop (SSW) · doi:10.21437/ssw.2021-10 · Cited by 5

Personalized Audiobook Generation Using Voice Cloning and Text-to-Speech Synthesis

Wei, C.-C., Hung, L.-C., Gao, S., Chen, Y.-C., & Tseng, S.-P. (2024) · International Conference on Orange Technology (ICOT) · doi:10.1109/icot64290.2024.10936951 · Cited by 2

A Low-Overhead Approach to Dynamic Frequency Scaling for GPUs Using Multi-Dimensional Energy Efficiency Curves

Wright, E., & Gopalan, A. (2025) · IEEE Conference on Technologies for Sustainability · doi:10.1109/sustech63138.2025.11025714 · Cited by 2

A Review of the State of the Child Speech Synthesis Landscape

Lazareva, V., Dimitrovska, M. M., Pagliara, S. M., Mavrou, K., Theodorou, E., Taškovski, D., Todorovska, D., Zanfardino, F., Spera, A., Mura, A., et al. (2025) · Springer eBooks · doi:10.1007/978-3-032-01632-4_9 · Cited by 2

Swar (Hindi): A Speaker-Aware Vocoder for Low-Resource Speech Synthesis

Purohit, R. M., & Patil, H. A. (2025) · International Conference on Asian Language Processing · doi:10.1109/ialp68296.2024.11156272 · Cited by 2

An Overview of Accent Conversion Techniques from Statistical and Deep Learning: Its Advantages and Limitations

Shrestha, A., Ghorshi, S., & Panahi, I. M. S. (2025) · Circuits Systems and Signal Processing · doi:10.1007/s00034-025-03346-9 · Cited by 2

Multi-Scale Self-Supervised Learning for Efficient Audio Deepfake Detection

Wani, T. M., & Amerini, I. (2025) · IEEE Signal Processing Letters · doi:10.1109/lsp.2025.3634032 · Cited by 2

The Personalization Paradox: Trade-offs Between Social Presence and Task Efficiency in Embodied AR Instructors

Mohammed, A. M., McCarthy, M., Neumann, C., Bruder, G., Reiners, D., & Cruz‐Neira, C. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791902 · Cited by 3

Deepfakes: A comprehensive survey on techniques, challenges and future directions

Usmani, S., Kumar, D. S., & Sadhya, D. (2026) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2026.111210 · Cited by 3

Personalized End-to-End Mandarin Speech Synthesis using Small-sized Corpus

Yuan, C., & Huang, Y. (2020) · Cited by 2

A Fast and Lightweight Speech Synthesis Model based on FastSpeech2

Nguyen, H.-K., Jeong, K., & Kang, H.-G. (2021) · International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) · doi:10.1109/itc-cscc52171.2021.9501479 · Cited by 2

Involution Based Speech Autoencoder: Investigating the Advanced Vision Operator Performance on Speech Feature Extraction

Zhong, T., Velazquez, I. M., & Haneda, Y. (2021) · IEEE Global Conference on Consumer Electronics (GCCE) · doi:10.1109/gcce53005.2021.9621826 · Cited by 2

Japanese Neural Incremental Text-to-Speech Synthesis Framework With an Accent Phrase Input

Yanagita, T., Sakti, S., & Nakamura, S. (2023) · IEEE Access · doi:10.1109/access.2023.3251657 · Cited by 2

Neural Diffeomorphic Non-uniform B-spline Flows

Hong, S., & Chun, S. Y. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i10.26441 · Cited by 2

LIUM-TTS entry for Blizzard 2023

Saget, F., Gaudier, T., Shamsi, M., & Tahon, M. (2023) · doi:10.21437/blizzard.2023-2 · Cited by 2

Synthetic Speaking Children – Why We Need Them and How to Make Them

Farooq, M. A., Bigioi, D., Jain, R., Wang, Y., Yiwere, M. Y., & Corcoran, P. (2023) · International Conference on Speech Technology and Human-Computer Dialogue (SpeD) · doi:10.1109/sped59241.2023.10314943 · Cited by 2

Advancing Limited Data Text-to-Speech Synthesis: Non-Autoregressive Transformer for High-Quality Parallel Synthesis

Al-Radhi, M. S., Ibrahim, O., Mandeel, A. R., Csapó, T. G., & Németh, G. (2023) · International Conference on Speech Technology and Human-Computer Dialogue (SpeD) · doi:10.1109/sped59241.2023.10314948 · Cited by 2

Improved Child Text-to-Speech Synthesis through Fastpitch-based Transfer Learning

Jain, R., & Corcoran, P. (2023) · International Conference on Speech Technology and Human-Computer Dialogue (SpeD) · doi:10.1109/sped59241.2023.10314899 · Cited by 2

A Generative Modelling-based Approach for Text-to-Speech Synthesis in Romanian Language

Casian, M., & Czibula, G. (2023) · IEEE International Conference on Intelligent Computer Communication and Processing (ICCP) · doi:10.1109/iccp60212.2023.10398699 · Cited by 2

Energy-Based Models for Speech Synthesis

Sun, W., Tu, Z., & Ragni, A. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10447218 · Cited by 2

Research progress on speech deepfake and its detection techniques

Xu, Y., Li, B., Tan, S., & Huang, J. (2024) · Journal of Image and Graphics · doi:10.11834/jig.230476 · Cited by 4

TinyVocos: Neural Vocoders on MCUs

Ciapponi, S., Paissan, F., Ancilotto, A., & Farella, E. (2024) · IEEE International Symposium on the Internet of Sounds (IS2) · doi:10.1109/is262782.2024.10704173 · Cited by 2

Interactive Multimedia Association-Adaptive Differential Pulse Code Modulation Codec With Gated Recurrent Unit Predictor

Sheferaw, G. K., Mwangi, W. R., Kimwele, M. W., Mamuye, A. L., & Salau, A. O. (2024) · IEEE Access · doi:10.1109/access.2024.3493604 · Cited by 2

Emotional Text-To-Speech in Japanese Using Artificially Augmented Dataset

Khalifah, M. J. A., Ptaszynski, M. E., & Masui, F. (2024) · IEEE Access · doi:10.1109/access.2024.3495694 · Cited by 2

Leveraging Low-Rank Adaptation for Parameter-Efficient Fine-Tuning in Multi-Speaker Adaptive Text-to-Speech Synthesis

Hong, C., Lee, J. H., & Kim, H. K. (2024) · IEEE Access · doi:10.1109/access.2024.3515206 · Cited by 2

Fast Neural Vocoder With Fundamental Frequency Control Using Finite Impulse Response Filters

Ohtani, Y., Okamoto, T., Toda, T., & Kawai, H. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3564048 · Cited by 2

Combined generative and predictive modeling for speech super-resolution

Wang, H., Healy, E. W., & Wang, D. (2025) · Computer Speech & Language · doi:10.1016/j.csl.2025.101808 · Cited by 4

End-to-End Multi-Speaker FastSpeech2 With Hierarchical Decoder

Adibian, M., & Zeinali, H. (2025) · IEEE Access · doi:10.1109/access.2025.3589120 · Cited by 2

Wavehax: Aliasing-Free Neural Waveform Synthesis Based on 2D Convolution and Harmonic Prior for Reliable Complex Spectrogram Estimation

Yoneyama, R., Miyashita, A., Yamamoto, R., & Toda, T. (2025) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/taslpro.2025.3624985 · Cited by 2

Spectral and Latent Speech Representation Distortion for TTS Evaluation

Kongthaworn, T., Naowarat, B., & Chuangsuwanich, E. (2021) · Interspeech (USB) · doi:10.21437/interspeech.2021-2258 · Cited by 2

Analysis of Conversational Speech with Application to Voice Adaptation

Mukherjeee, B., Prakash, A., & Murthy, H. A. (2021) · IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) · doi:10.1109/asru51503.2021.9688146 · Cited by 2

Text to Speech System for Lambani - A Zero Resource, Tribal Language of India

Dasare, A., Deepak, K. T., Prasanna, M., & Vijaya, K. (2022) · International Conference on Speech Database and Assessments · doi:10.1109/o-cocosda202257103.2022.9997838 · Cited by 2

An objective evaluation of the effects of recording conditions and speaker characteristics in multi-speaker deep neural speech synthesis

Lőrincz, B., Stan, A., & Giurgiu, M. (2021) · Procedia Computer Science · doi:10.1016/j.procs.2021.08.078 · Cited by 5

Synthesizing waveform sequence-to-sequence to augment training data for sequence-to-sequence speech recognition

Ueno, S., Mimura, M., Sakai, S., & Kawahara, T. (2021) · Nippon Onkyo Gakkaishi/Acoustical science and technology/Nihon Onkyo Gakkaishi · doi:10.1250/ast.42.333 · Cited by 2

DEEPA: A Deep Neural Analyzer for Speech and Singing Vocoding

Nikonorov, S., Şişman, B., Zhang, M., & Li, H. (2021) · IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) · doi:10.1109/asru51503.2021.9687923 · Cited by 2

Practical Cognitive Speech Compression

Lotfidereshgi, R., & Gournay, P. (2022) · IEEE Data Science Workshop (DSW) · doi:10.1109/dslw53931.2022.9820506 · Cited by 2

AIELSON: A neural spoken-word poetry generator with a distinct South American voice

del Prado, P. T. N. (2022) · Journal of Interdisciplinary Voice Studies · doi:10.1386/jivs_00052_1 · Cited by 2

VStyclone: Real-time Chinese voice style clone

Wu, Y., Zhao, H., Liang, X., & Sun, Y. (2022) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2022.108534 · Cited by 3

Machine learning assisted composition of traditional music from the Colombian Caribbean Region

Pico-Ripoll, D., Percybrooks, W., & Viloria-Núñez, C. (2022) · IEEE ANDESCON · doi:10.1109/andescon56260.2022.9989762 · Cited by 2

Dual ResNet-based Environmental Sound Classification using GAN

Jang, S., & Kim, Y. (2023) · International Conference on Ubiquitous Information Management and Communication (IMCOM) · doi:10.1109/imcom56909.2023.10035597 · Cited by 2

Improve GAN-based Neural Vocoder using Truncated Pointwise Relativistic Least Square GAN

Li, Y., & Wang, C. (2022) · International Conference on Advanced Information Science and System (AISS) · doi:10.1145/3573834.3574506 · Cited by 2

Development of a Kiswahili Text-to-Speech System Based on Tacotron 2 and WaveNet Vocoder

Rono, K. K., Maina, C. W., & Mwangi, E. (2022) · International Journal of Electrical and Electronics Engineering · doi:10.14445/23488379/ijeee-v10i2p107 · Cited by 2

Language Learning using Caption Generation within Reciprocal Multi-Party Child-Tutor-Tutee Interaction

Aimysheva, A., Bekkuliyev, M., Karasheva, M., Oralbayeva, N., Amirova, A., Bruno, B., & Sandygulova, A. (2023) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3568294.3580176 · Cited by 2

Data Augmentation Methods on Ultrasound Tongue Images for Articulation-to-Speech Synthesis

Ibrahimov, I., Gosztolya, G., & Csapó, T. G. (2023) · ISCA Speech Synthesis Workshop (SSW) · doi:10.21437/ssw.2023-36 · Cited by 2

Minimization of noise annoyance from exhaust-system tailpipes through acoustic signal analysis

Zhang, J., Luo, J. G., Fu, A. J., Zhang, G. S., & Yang, D. (2023) · Applied Acoustics · doi:10.1016/j.apacoust.2023.109692 · Cited by 2

Enhancing End-to-End Speech Synthesis by Modeling Interrogative Sentences with Speaker Adaptation

Mandeel, A. R., Al-Radhi, M. S., & Csapó, T. G. (2023) · International Conference on Speech Technology and Human-Computer Dialogue (SpeD) · doi:10.1109/sped59241.2023.10314910 · Cited by 2

Machine learning at the edge to improve in-field safeguards inspections

Shoman, N., Williams, K., Balsara, B., Ramakrishnan, A., Kakish, Z., Coram, J. L., Honnold, P., Rivas, T., & Smartt, H. A. (2024) · Annals of Nuclear Energy · doi:10.1016/j.anucene.2024.110398 · Cited by 2

Lightweight, Multi-Speaker, Multi-Lingual Indic Text-to-Speech

Singh, A., Nagireddi, A., Deekshitha, G., Bandekar, J., Roopa, R., Badiger, S., Udupa, S., Ghosh, P. K., Murthy, H. A., Zen, H., et al. (2023) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp49357.2023.10433926 · Cited by 2

A Study on Combining Non-Parallel and Parallel Methodologies for Mandarin-English Cross-Lingual Voice Conversion

You, C. H., & Dong, M. (2024) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp48485.2024.10446264 · Cited by 2

Can We Trust Deep Speech Prior?

Shi, Y., Chen, H., Tang, Z., Li, L., Wang, D., & Han, J. (2021) · IEEE Spoken Language Technology Workshop (SLT) · doi:10.1109/slt48900.2021.9383499 · Cited by 2

Challenges for Edge-AI Implementations of Text-To-Speech Synthesis

Bigioi, D., & Corcoran, P. (2021) · International Conference on Consumer Electronics · doi:10.1109/icce50685.2021.9427679 · Cited by 2

How to Make Text-to-Speech System Pronounce "Voldemort": an Experimental Approach of Foreign Word Phonemization in Vietnamese

Mạc, Đ.-K., Nguyen, V., Nguyen, D.-N., & NGUYEN, K.-A. (2021) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp39728.2021.9414386 · Cited by 2

Perception of smiling voice in spontaneous speech synthesis

Kirkland, A., Włodarczak, M., Gustafson, J., & Székely, É. (2021) · ISCA Speech Synthesis Workshop (SSW) · doi:10.21437/ssw.2021-19 · Cited by 2

Learning Vietnamese-English Code-Switching Speech Synthesis Model Under Limited Code-Switched Data Scenario

Nguyen, C. M., Phung, L. V., Bui, C. T., Truong, T. V., & Nguyen, T.-H. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-89363-7_12 · Cited by 2

NeuralDPS: Neural Deterministic Plus Stochastic Model With Multiband Excitation for Noise-Controllable Waveform Generation

Wang, T., Fu, R., Yi, J., Tao, J., & Wen, Z. (2022) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2022.3140480 · Cited by 2

Dreamsound: Deep Activation Layer Sonification

Halac, F. N. C., & Delgadino, M. (2021) · International Conference on Auditory Display (ICAD) · doi:10.21785/icad2021.032 · Cited by 2

Unsupervised Style and Content Separation by Minimizing Mutual Information for Speech SynthesisPreprint

Hu, T.-Y., Shrivastava, A., Tuzel, O., & Dhir, C. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2003.06227 · Cited by 2

Efficient, end-to-end and self-supervised methods for speech processing and generation

Pascual, S. (2020) · doi:10.5821/dissertation-2117-180792 · Cited by 2

Auto-decoding GraphsPreprint

Shah, S., & Koltun, V. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2006.02879 · Cited by 2

PPSpeech: Phrase based Parallel End-to-End TTS SystemPreprint

Cong, Y., Zhang, R., & Luan, J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.02490 · Cited by 2

Parallel waveform synthesis based on generative adversarial networks with voicing-aware conditional discriminatorsPreprint

Yamamoto, R., Song, E., Hwang, M.-J., & Kim, J.-M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.14151 · Cited by 2

Towards transformation-resilient provenance detection of digital mediaPreprint

Hayes, J., Krishnamurthy, Dvijotham, Chen, Y., Dieleman, S., Kohli, P., & Casagrande, N. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.07355 · Cited by 2

MelGlow: Efficient Waveform Generative Network Based on Location-Variable ConvolutionPreprint

Zeng, Z., Wang, J., Cheng, N., & Xiao, J. Z. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.01684 · Cited by 2

FBWave: Efficient and Scalable Neural Vocoders for Streaming Text-To-Speech on the EdgePreprint

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