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In this paper, we propose reverse inference optimization (RIO), a simple and effective method designed to enhance the robustness of autoregressive-model-based zero-shot text-to-speech (TTS) systems using reinforcement learning from human feedback (RLHF).
Adaptation of context-dependent deep neural networks for automatic speech recognition
Kaisheng Yao, Dong Yu, Frank Seide, Hang Su, Li Deng, and Yifan Gong · 2012
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Scheduled sampling for sequence prediction with recurrent neural networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer · 2015
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Librispeech: an asr corpus based on public domain audio books
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur · 2015
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Libritts: A corpus derived from librispeech for text-to-speech
Heiga Zen, Viet Dang, Rob Clark, Yu Zhang, Ron J Weiss, Ye Jia, Zhifeng Chen, and Yonghui Wu · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Gigaspeech: An evolving, multi-domain asr corpus with 10,000 hours of transcribed audio
Guoguo Chen, Shuzhou Chai, Guanbo Wang, Jiayu Du, Wei-Qiang Zhang, Chao Weng, Dan Su, Daniel Povey, Jan Trmal, Junbo Zhang, et al · 2021
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Context-aware selective label smoothing for calibrating sequence recognition model
Shuangping Huang, Yu Luo, Zhenzhou Zhuang, Jin-Gang Yu, Mengchao He, and Yongpan Wang · 2021
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Text generation by learning from demonstrations
Richard Yuanzhe Pang and He He · 2021
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Soundstream: An end-to-end neural audio codec
Neil Zeghidour, Alejandro Luebs, Ahmed Omran, Jan Skoglund, and Marco Tagliasacchi · 2021
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al · 2022
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Generalization ability of mos prediction networks
Erica Cooper, Wen-Chin Huang, Tomoki Toda, and Junichi Yamagishi · 2022
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Self-supervised speech representation learning: A review
Abdelrahman Mohamed, Hung-yi Lee, Lasse Borgholt, Jakob D Havtorn, Joakim Edin, Christian Igel, Katrin Kirchhoff, Shang-Wen Li, Karen Livescu, Lars Maaløe, et al · 2022
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Introducing chatgpt
OpenAI · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Better speech synthesis through scaling
James Betker · 2023
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Audiolm: a language modeling approach to audio generation
Zalán Borsos, Raphaël Marinier, Damien Vincent, Eugene Kharitonov, Olivier Pietquin, Matt Sharifi, Dominik Roblek, Olivier Teboul, David Grangier, Marco Tagliasacchi, et al · 2023
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Safe rlhf: Safe reinforcement learning from human feedback
Josef Dai, Xuehai Pan, Ruiyang Sun, Jiaming Ji, Xinbo Xu, Mickel Liu, Yizhou Wang, and Yaodong Yang · 2023
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High fidelity neural audio compression
Alexandre Défossez, Jade Copet, Gabriel Synnaeve, and Yossi Adi · 2023
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Repcodec: A speech representation codec for speech tokenization
Zhichao Huang, Chutong Meng, and Tom Ko · 2023
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Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung · 2023
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Speak, read and prompt: High-fidelity text-to-speech with minimal supervision
Eugene Kharitonov, Damien Vincent, Zalán Borsos, Raphaël Marinier, Sertan Girgin, Olivier Pietquin, Matt Sharifi, Marco Tagliasacchi, and Neil Zeghidour · 2023
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Speak foreign languages with your own voice: Cross-lingual neural codec language modeling
Ziqiang Zhang, Long Zhou, Chengyi Wang, Sanyuan Chen, Yu Wu, Shujie Liu, Zhuo Chen, Yanqing Liu, Huaming Wang, Jinyu Li, et al · 2023
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Direct preference optimization with an offset
Afra Amini, Tim Vieira, and Ryan Cotterell · 2024
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Enhancing zero-shot text-to-speech synthesis with human feedback
Chen Chen, Yuchen Hu, Wen Wu, Helin Wang, Eng Siong Chng, and Chao Zhang · 2024
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Self-play fine-tuning converts weak language models to strong language models
Zixiang Chen, Yihe Deng, Huizhuo Yuan, Kaixuan Ji, and Quanquan Gu · 2024
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Generating images with multimodal language models
Jing Yu Koh, Daniel Fried, and Russ R Salakhutdinov · 2023
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Promptstyle: Controllable style transfer for text-to-speech with natural language descriptions
Guanghou Liu, Yongmao Zhang, Yi Lei, Yunlin Chen, Rui Wang, Zhifei Li, and Lei Xie · 2023
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OpenAI · 2023
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Audiopalm: A large language model that can speak and listen
Paul K Rubenstein, Chulayuth Asawaroengchai, Duc Dung Nguyen, Ankur Bapna, Zalán Borsos, Félix de Chaumont Quitry, Peter Chen, Dalia El Badawy, Wei Han, Eugene Kharitonov, et al · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, et al · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, et al · 2023
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Neural codec language models are zero-shot text to speech synthesizers
Chengyi Wang, Sanyuan Chen, Yu Wu, Ziqiang Zhang, Long Zhou, Shujie Liu, Zhuo Chen, Yanqing Liu, Huaming Wang, Jinyu Li, et al · 2023
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Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, and Douwe Kiela · 2024
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Textrolspeech: A text style control speech corpus with codec language text-to-speech models
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Base tts: Lessons from building a billion-parameter text-to-speech model on 100k hours of data
Mateusz Łajszczak, Guillermo Cámbara, Yang Li, Fatih Beyhan, Arent van Korlaar, Fan Yang, Arnaud Joly, Álvaro Martín-Cortinas, Ammar Abbas, Adam Michalski, et al · 2024
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Direct preference optimization: Your language model is secretly a reward model
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Self-rewarding language models
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Token-level direct preference optimization
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Anygpt: Unified multimodal llm with discrete sequence modeling
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Speechalign: Aligning speech generation to human preferences
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