--- title: "Who cites WaveGlow: A Flow-based — 83 citing papers" description: "83 papers of the Elamur Research library cite «WaveGlow: A Flow-based Generative Network for Speech Synthesis», found in their…" canonical: "https://research.elamur.ai/free/en/papers/prenger-2018-waveglow-flow-based-generative-network/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/prenger-2018-waveglow-flow-based-generative-network/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [WaveGlow: A Flow-based Generative Network for…](https://md.research.elamur.ai/free/en/papers/prenger-2018-waveglow-flow-based-generative-network/) / cited by # Who cites «WaveGlow: A Flow-based Generative Network for Speech Synthesis» 83 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «WaveGlow: A Flow-based Generative Network for Speech Synthesis»](https://md.research.elamur.ai/free/en/papers/prenger-2018-waveglow-flow-based-generative-network/) 1. [**HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis arXiv:2010.05646**Jungil Kong, Jaehyeon Kim, Jaekyoung Bae*2020 · 969 citations*](https://md.research.elamur.ai/free/en/papers/kong-2020-hifi-gan-generative-adversarial-networks/) 2. [**Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers arXiv:2301.02111**Chengyi Wang, Sanyuan Chen, Yu Wu, et al.*2023 · 335 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-neural-codec-language-models-zero/) 3. **[FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow](https://md.research.elamur.ai/free/en/papers/ma-2019-flowseq-non-autoregressive-conditional-sequence/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuezhe Ma, Chunting Zhou, Xian Li, et al.*2019 · 218 citations* 4. **[High-Fidelity Audio Compression with Improved RVQGAN](https://md.research.elamur.ai/free/en/papers/kumar-2023-high-fidelity-audio-compression-improved/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rithesh Kumar, Prem Seetharaman, Alejandro Luebs, et al.*2023 · 196 citations* 5. **[On Generative Spoken Language Modeling from Raw Audio](https://md.research.elamur.ai/free/en/papers/lakhotia-2021-generative-spoken-language-modeling-raw/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Kushal Lakhotia, Eugene Kharitonov, Wei-Ning Hsu, et al.*2021 · 170 citations* 6. **[Recent Advances in Speech Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/cui-2025-recent-advances-speech-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqian Cui, Dianzhi Yu, Xiaoqi Jiao, et al.*2025 · 69 citations* 7. **[NatiQ: An End-to-end Text-to-Speech System for Arabic](https://md.research.elamur.ai/free/en/papers/abdelali-2022-natiq-end-end-text-speech/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Ahmed Abdelali, Nadir Durrani, Cenk Demiroglu, et al.*2022 · 16 citations* 8. **[Controlling Prosody in End-to-End TTS: A Case Study on Contrastive Focus Generation](https://md.research.elamur.ai/free/en/papers/latif-2021-controlling-prosody-end-end-tts/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Siddique Latif, Inyoung Kim, Ioan Calapodescu, et al.*2021 · 10 citations* 9. **[PhonemeDF: A Synthetic Speech Dataset for Audio Deepfake Detection and Naturalness Evaluation](https://md.research.elamur.ai/free/en/papers/nallaguntla-2026-phonemedf-synthetic-speech-dataset-audio/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Vamshi Nallaguntla, Aishwarya R. Fursule, Shruti Kshirsagar, et al.*2026 · 2 citations* 10. **[AraSpot: Arabic Spoken Command Spotting](https://md.research.elamur.ai/free/en/papers/salhab-2023-araspot-arabic-spoken-command-spotting/) [ACM Transactions on Asian and Low-Resource Language Information Processing](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-asian-and-low-resource-language-information-processing/)**Mahmoud Salhab, Haidar Harmanani*2023 · 1 citation* 11. **[A Benchmark Dataset and Comparative Evaluation of Phonemized and Romanized Urdu for Text-to-Speech](https://md.research.elamur.ai/free/en/papers/shahid-2026-benchmark-dataset-comparative-evaluation-phonemized/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**M Kaab Bin Shahid, Muhammed Izharuddin*2026* 12. **[Beyond Unified Models: A Service-Oriented Approach to Low Latency, Context Aware Phonemization for Real Time TTS](https://md.research.elamur.ai/free/en/papers/qharabagh-2026-beyond-unified-models-service-oriented/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mahta Fetrat Qharabagh, Donya Navabi, Zahra Dehghanian, et al.*2026* 13. **[German-Arabic Speech-to-Speech Translation for Psychiatric Diagnosis](https://md.research.elamur.ai/free/en/papers/hussain-2020-german-arabic-speech-speech-translation/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Juan Hussain, Mohammed Mediani, Moritz Behr, et al.*2020* 70 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/prenger-2018-waveglow-flow-based-generative-network/) — WaveGlow: A Flow-based Generative Network for Speech Synthesis