Aural Authenticity of Virtual Reality Documentary Made in 3D Virtual Environment
Bibliographic record
Abstract
The concept of documentary is a 'notoriously slippery eel', or even the slipperiest one in the history of cinema (Kahana, 2016). Movies inside virtual reality are one of the promising talked-about areas in the VR industry. With the involvement of virtual reality in the production of documentaries, the dialectic between virtuality and authenticity makes this concept of documentary even more elusive, especially for VR documentaries made in 3D. In the viewing experience, the virtual environment is built upon computing 'true depth'. This virtual cinematic space is set up through the modelling in software (e.g. Maya and 3D Max) and then to 3D engine (e.g. Unity or Unreal). Therefore, a dialectical critique arises: Do documentary exists in VR films? When the spaces and mise-en-scène of the documentary are all artificially created through computing software, whether it can still be considered as an authentic form of documentary? How can this sub-genre of documentary continue to exist as a kind of proclaimed ‘non-fiction’ when the film is based entirely on fictional visual input? The current discussion on the realistic qualities of VR documentaries focuses on the questioning on the virtual nature of the visual environment and neglects that listening is also part of the experience in this VE. So, is it possible to understand the authenticity of the VR documentary from the perspective of auditory system? This paper provides a perspective for understanding the auditory authenticity of non-fictional restoration of virtual environments (VE) in virtual reality (VR) documentaries. Such a perspective argues that although the VR documentaries are made with 3D modelling and computing engine, their authenticity in sound remains in line with the documentary principle. In the sound design perspective, it simultaneously creates a non-fictional soundscape to reproduce the ‘genius loci’ (spirit of place) based on the real individual perception in history. In the first part of paper, we review how the documentary film has set itself apart as a non-fictional genre based on Bill Nichols’s analysis of the boundary between traditional documentary and its counterparts in cinema. And then we place this principle on aural reality in the context of HRCS (Head-Related Coordinate System) and HRTF (Head-Related Transfer Function) to argue VR documentary as a sub-genre of the documentary film in aural technical basis. In the second part, we explore the concept of ‘soundscape’ in the sound design of VR documentaries, analysing how such a virtual sound environment establishes an authentic spirit of space in the case of Anne Frank House VR. This study only explores the auditory sound in virtual places, and does not address the discussion of artificial fictional sounds outside cinematic space (e.g. music, voice-overs, UI Panel sounds.)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".