Bibliography and Research & Learning Centres

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Sources, references, and further reading. AI-generated using ChatAI. Use subject to ChatAI Terms of Service.

The study of synthetic performance draws on an unusually wide range of disciplines: acting theory, animation, computer graphics, gesture studies, rhetoric, anatomy, motion capture, game design, voice synthesis, ethics, and artificial intelligence. The resources listed below reflect that breadth, and have been substantially revised and extended in 2026 to address developments in the field since the guild’s last bibliographic update in 2013. This page also serves as the house style reference for contributors.

Journals · Books and Articles · Anatomy · Motion Capture · Rigging · Artificial Intelligence & Neural Animation · Voice Synthesis · Ethics, Rights & Authorship · Further Reading · Research & Learning Centres

Journals

  • Gesture (John Benjamins Publishing) — the principal peer-reviewed journal for gesture studies; indexed in WoS, Scopus and MLA.
  • International Journal of Human Factors Modelling and Simulation (IJHFMS)
  • ACM Transactions on Graphics — the leading venue for advances in computer graphics and animation, including character simulation.
  • IEEE Transactions on Visualization and Computer Graphics
  • Computer Animation and Virtual Worlds (Wiley)
  • AI & Society (Springer) — covers the social, cultural and ethical dimensions of artificial intelligence.
  • Journal of Artificial Intelligence Research (JAIR) — open access.

Books and Articles (general)

  • Austin, Gilbert. Chironomia, or a Treatise on Rhetorical Delivery. London, 1806. Ed. Robb & Thonssen. Carbondale: Southern Illinois UP, 1966.
  • Blair, Preston. Cartoon Animation. Laguna Hills, CA: Walter Foster, 1980.
  • Bulwer, John. Chirologia / Chironomia. London, 1644.
  • Cienki, Alan (ed.). The Cambridge Handbook of Gesture Studies. Cambridge: Cambridge UP, 2024. — New: the most comprehensive current reference work in the field.
  • De Jorio, Andrea. Gesture in Naples and Gesture in Classical Antiquity. Trans. Adam Kendon. 2002.
  • Ekman, Paul. Facial Action Coding System.
  • Goldin-Meadow, Susan. Hearing Gesture. Cambridge, MA: Harvard UP, 2003.
  • Goldin-Meadow, Susan. Thinking with Your Hands: The Surprising Science Behind How Gestures Shape Our Thoughts. New York: Basic Books, 2023. — New: accessible synthesis of decades of gesture research, directly relevant to the design of expressive synthetic agents.
  • Hooks, Ed. Acting for Animators. 4th ed. London: Routledge, 2017. — Updated edition; the standard text for the field.
  • Kendon, Adam. Gesture: Visible Action as Utterance. Cambridge: Cambridge UP, 2004.
  • Magnenat-Thalmann, Nadia et al. Synthetic Actors in Computer-Generated 3D Films. Berlin: Springer-Verlag, 1990.
  • Mateas, Michael. “Expressive AI: Games and Artificial Intelligence.” DiGRA Conference Proceedings, 2003.
  • McCloud, Scott. Understanding Comics. Northampton, MA, 1993.
  • McNeill, David. Hand and Mind. Chicago: University of Chicago Press, 1992.
  • McNeill, David. Gesture and Thought. Chicago: University of Chicago Press, 2005.
  • Muybridge, Eadweard. Complete Human and Animal Locomotion. New York: Dover, 1979.
  • Osipa, Jason. Stop Staring: Facial Modeling and Animation Done Right. 2nd ed. Indianapolis: Wiley, 2007.
  • Thomas, Frank and Ollie Johnston. The Illusion of Life: Disney Animation. New York: Disney Editions, 1981.
  • White, Tony. The Animator’s Workbook. Oxford: Phaidon Press, 1986.

Anatomy

  • Bridgman, George. Constructive Anatomy. New York: Dover, 1920.
  • Peck, Stephen. Atlas of Human Anatomy for the Artist. Oxford: OUP, 1951.
  • Rubins, David. The Human Figure: An Anatomy for Artists. New York: Penguin, 1953.

Motion Capture

  • Kitagawa, Midori and Brian Windsor. MoCap for Artists. Oxford: Focal Press, 2008.
  • Magnenat-Thalmann, Nadia and Daniel Thalmann (eds). Handbook of Virtual Humans. Chichester: Wiley, 2004.
  • Menache, Alberto. Understanding Motion Capture. London: Academic Press, 2000.
  • Parent, Rick. Computer Animation Complete. Burlington: Morgan Kaufmann, 2009.
  • Rosenhahn, Bodo et al (eds). Human Motion: Understanding, Modelling, Capture, and Animation. Berlin: Springer, 2007.
  • Tevet, Guy et al. “Human Motion Diffusion Model.” ICLR 2023. — New: influential paper on diffusion-model-based motion generation, freely available at arxiv.org.
  • Zhang, Mingyuan et al. “MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model.” IEEE TPAMI, 2024. — New: state-of-the-art text-to-motion synthesis.

Rigging

  • Allen, Eric et al. Body Language: Advanced 3D Character Rigging. Indianapolis: Sybex, 2008.
  • Lehrman, Paul David. “The Digital Actor: Rigging, Performance and the Limits of Likeness.” Computer Animation and Virtual Worlds, 2019. — New: addresses the gap between technical rigging capability and expressive performance range.

Artificial Intelligence & Neural Animation

This section is new. The rapid development of machine learning methods for character animation, facial synthesis, and embodied AI agents has transformed the field since 2013. The entries below represent key landmarks.

  • Goodfellow, Ian et al. “Generative Adversarial Networks.” Advances in Neural Information Processing Systems (NeurIPS), 2014. — The foundational GAN paper; the method underlies a significant portion of current face and body synthesis work.
  • Ho, Jonathan et al. “Denoising Diffusion Probabilistic Models.” NeurIPS, 2020. — Established diffusion models as the leading approach to high-quality image and motion generation.
  • Karras, Tero et al. “A Style-Based Generator Architecture for Generative Adversarial Networks” (StyleGAN). CVPR, 2019. — Introduced fine-grained control over synthetic face generation; versions 2 and 3 followed in 2020 and 2021.
  • Peng, Xue Bin et al. “DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills.” ACM SIGGRAPH, 2018. — Demonstrated that reinforcement learning can produce physically plausible character animation from reference motion clips.
  • Peng, Xue Bin et al. “AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control.” ACM SIGGRAPH, 2021. — Extended DeepMimic; now widely used in game engines for real-time character behaviour.
  • Radford, Alec et al. “Learning Transferable Visual Models from Natural Language Supervision” (CLIP). OpenAI, 2021. — Established cross-modal vision–language embeddings; widely used in text-driven animation pipelines.
  • Rombach, Robin et al. “High-Resolution Image Synthesis with Latent Diffusion Models.” CVPR, 2022. — The paper behind Stable Diffusion; enabled affordable high-quality image generation including character art.
  • Sohl-Dickstein, Jascha et al. “Deep Unsupervised Learning Using Nonequilibrium Thermodynamics.” ICML, 2015. — Early foundational work on diffusion-based generative models.
  • Thies, Justus et al. “Neural Voice Puppetry: Audio-driven Facial Reenactment.” ECCV, 2020. — Drove synthetic facial performance from audio alone; directly relevant to synactor voice-body integration.
  • Vaswani, Ashish et al. “Attention Is All You Need.” NeurIPS, 2017. — Introduced the transformer architecture; underlies virtually all large language and multimodal models now used in synthetic agent design.
  • Zhu, Jun-Yan et al. “Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks” (CycleGAN). ICCV, 2017. — Enabled style transfer between animation and photorealism without paired training data.

Voice Synthesis

This section is new. The synthesis of expressive, characterful voice has become central to the synthetic actor’s craft.

  • Arik, Serör O. et al. “Deep Voice: Real-time Neural Text-to-Speech.” ICML, 2017. — Baidu Research’s landmark paper establishing end-to-end neural TTS.
  • Casanova, Edresson et al. “YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for Everyone.” ICML, 2022. — Enables voice cloning from minimal data; raises significant questions for synthetic performance and consent.
  • Oord, Aaron van den et al. “WaveNet: A Generative Model for Raw Audio.” DeepMind, 2016. — Transformed the quality of neural voice synthesis; still influential in current pipelines.
  • Shen, Jonathan et al. “Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions” (Tacotron 2). Google, ICASSP, 2018.
  • Wang, Chengyi et al. “Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers” (VALL-E). Microsoft Research, 2023. — New: demonstrated three-second speaker cloning using large language model architecture; significant implications for synthetic identity and consent.

Ethics, Rights & Authorship

This section is new, reflecting the guild’s long-standing concern with the legal and ethical status of synthetic performers and the human counterparts whose labour underpins their existence.

  • Boden, Margaret A. AI: Its Nature and Future. Oxford: OUP, 2016.
  • Bridle, James. New Dark Age: Technology and the End of the Future. London: Verso, 2018. — A critical account of algorithmic culture relevant to questions of authorship and attribution in AI-generated performance.
  • Cave, Stephen and Kanta Dihal. “Hopes and Fears for Intelligent Machines in Fiction and Reality.” Nature Machine Intelligence, 2019.
  • Floridi, Luciano et al. “An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations.” Minds and Machines, 2018.
  • Gabriel, Iason. “Artificial Intelligence, Values, and Alignment.” Minds and Machines, 2020.
  • Gunkel, David J. Robot Rights. Cambridge, MA: MIT Press, 2018. — The most thorough philosophical treatment of the question of whether artificial entities can be moral patients; directly relevant to the guild’s concerns.
  • Pasquale, Frank. New Laws of Robotics: Defending Human Expertise in the Age of AI. Cambridge, MA: Harvard UP, 2020. — Argues for regulations that preserve human contribution in AI-assisted creative work; essential for understanding the policy environment synactors operate in.
  • Zuboff, Shoshana. The Age of Surveillance Capitalism. London: Profile Books, 2019. — Analyses the extraction of behavioural data from human subjects; relevant to the use of performer data in training synthetic agents.

Further Reading

  • Duncan, Jody. The Winston Effect. London: Titan Books, 2006.
  • Kurzweil, Ray. The Singularity Is Near. New York: Penguin, 2006.
  • Kurzweil, Ray. The Singularity Is Nearer. New York: Viking, 2024. — New: the long-awaited sequel, updating Kurzweil’s projections in light of developments in large language models and embodied AI.
  • Rickitt, Richard. Special Effects: The History and Technique. New York: Billboard Books, 2007.
  • Russell, Stuart. Human Compatible: Artificial Intelligence and the Problem of Control. New York: Viking, 2019. — New: accessible and rigorous account of the alignment problem; important context for anyone designing AI agents intended to interact with human performers.

Research & Learning Centres

Links have been verified and updated in 2026. Dead or significantly changed URLs from the 2013 edition are noted.

Modelling & Animation

  • Center for Human Modeling and Simulation, University of Pennsylvania — URL defunct as of 2026; research continues within the Penn Graphics group at cis.upenn.edu.
  • Disney Research — la.disneyresearch.com — Publishes regularly on character animation, physics simulation, and neural rendering.
  • SIGGRAPH Digital Library — dl.acm.org/conference/siggraph — Archive of all SIGGRAPH proceedings; the primary record of advances in computer animation.
  • Weta Digital Research — wetafx.co.nz — Publishes technical papers on crowd simulation (Massive), facial performance capture, and virtual production.

Gesture Studies

  • International Society for Gesture Studies — gesturestudies.com — URL updated from isgs.org, which now resolves to an unrelated organisation.
  • Goldin-Meadow Laboratory, University of Chicago — voices.uchicago.edu/goldinmeadowlab/ — URL updated; lab active and publishing.
  • McNeill Lab, University of Chicago — mcneilllab.uchicago.edu — Lab closed in 2017 following David McNeill’s retirement; the site is preserved as an archive of significant research materials.
  • Nijmegen Gesture Centre, Radboud University / Max Planck Institute for Psycholinguistics — nijmegengesturecentre.org — URL updated; centre active, co-directed by Asli Ozyurek and Judith Holler.
  • Max Planck Institute for Psycholinguistics, Multimodal Language Department — mpi.nl — New: the MPI’s dedicated department for gesture, sign and multimodal communication research.

Artificial Intelligence & Machine Learning

  • Papers With Code — paperswithcode.com — New: tracks state-of-the-art results in machine learning with linked code; invaluable for following developments in motion generation, face synthesis and neural animation.
  • Hugging Face — huggingface.co — New: the leading open-source repository for AI models, datasets and research; includes models directly relevant to synthetic voice, face generation and motion.
  • arXiv (cs.GR, cs.CV, cs.AI sections) — arxiv.org — New: preprint server where the majority of significant AI and graphics research appears before or instead of journal publication.
  • AI Ethics Lab — aiethicslab.com — New: research and policy work on the ethical dimensions of AI; relevant to questions of consent, attribution, and synthetic identity.

Voice Synthesis & Audio

  • ElevenLabs Research — elevenlabs.io/research — New: publishes technical work on expressive voice synthesis and cloning; at the frontier of what is currently possible in synthetic voice performance.
  • Coqui TTS (open source) — github.com/coqui-ai/TTS — New: open-source text-to-speech library supporting dozens of models; important for practitioners working without commercial infrastructure.

Other

  • Handspeak (ASL resources) — handspeak.com
  • SAG-AFTRA AI resources — sagaftra.org/artificial-intelligence — New: the US performers’ union’s evolving policy position on AI-generated performance, digital likeness rights, and consent; directly relevant to the guild’s concerns.
  • Equity (UK) — equity.org.uk — New: the UK performers’ union’s AI campaign pages; relevant for members working in British production contexts.