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verbal_morality_statue [2017/11/14 23:30] – tatoeba kratenko | projects:verbal_morality_statute [2023/12/29 02:58] – deepnemo | ||
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- | ====== Verbal Morality | + | ====== Verbal Morality |
- | ===== General Function ===== | + | **Documentation is WIP @ 37c3 - please consult nemo / rey / kratenko for questions** |
+ | |||
+ | The VMSE 2000 is the newest iteration in a long standing series of verbal hate crime prevention devices. It is able to detect language violations in all languages for the region of purchase and works in a range of up to 6 meters, while being able to work in conjunction with other instances of the VMSE2000 to cover your available space and keep you safe from dreaded language violations. | ||
+ | |||
+ | Our analysts predict that the device integrate into everyone' | ||
- | The VMSE2000 is the newest iteration in a long standing series of verbal hate crime prevention devices. It is able to detect language violations in all languages for the region of purchase and works in a range of up to 6 meters, while being able to work in conjunction with other instances of the VMSE2000 to cover your available space and keep you safe from dreaded language violations. | ||
===== Detailed Specification ===== | ===== Detailed Specification ===== | ||
- | * The VMSE2000 | + | * The VMSE 2000 listens for speech input and detects |
- | * Consequences of a detected language violation is a verbal notification as well as a printed receipt for a credit fine of 1$ in BTC including | + | * Consequences of a detected language violation is a verbal notification as well as a printed receipt for a credit fine of a sum adequate |
- | * The language | + | * The morality |
+ | * The public display of the maniacs moral misdemeanour will apply social pressure on the maniac, leading to an adjustment of the subjects moral values. | ||
+ | * The continuous enforcement of the verbal morality statute by the VMSE 2000 will result in a better society for everyone' | ||
- | ===== What needs to be done ===== | ||
- | Minimum Viable Product: | + | ===== Development ===== |
- | * evaluate Kaldi | + | The VMSE 2000 is one of the most important projects by Deep Cyber, if not one of the most important efforts of our lifetime. While the physical parameters and technical details |
- | * does it still have pre-trained models? | + | |
- | * does it run on a Raspi? | + | ====== Hardware ====== |
- | * find alternatives to Kaldi | + | |
- | * data set of language | + | - Raspberry Pi 5 (4 also successfully tested) |
- | * dict.cc | + | - Thermal Printer (compatible with `python-escpos`) |
- | * leo | + | - USB Audio Adapter |
- | * movie dataset? | + | - PlayStation Eye USB camera for (taped-over CCD) |
- | * there should | + | |
- | * ensure passable noise robustness | + | ====== Software used ====== |
+ | |||
+ | - OpenAI whisper model (base) prompted for your language | ||
+ | - [[https:// | ||
+ | - [https:// | ||
+ | |||
+ | ====== Source Code ====== | ||
+ | |||
+ | You can find the firmware / device glue at [[https:// | ||
+ | The voice detection part can be found at [[https:// | ||
+ | |||
+ | ===== Previous Iterations ===== | ||
+ | |||
+ | There were a lot of iterations | ||
+ | We tested DeepSpeech, DeepSpeech V2, RNN on DeepSpeech 2 feature extractors and binary classification RNNs trained from scratch. In the end the simplest and most robust model was OpenAI whisper. Our suspicion is that the amount of data, it's variance and the resulting | ||
- | ===== Design ===== | ||
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==== Data ==== | ==== Data ==== | ||
- | * [[https:// | + | |
+ | * https:// | ||
+ | * http:// | ||
+ | * https:// | ||
+ | * https:// | ||
+ | * //Sentiment analyses of single words or short phrases// unter https:// | ||
==== SW ==== | ==== SW ==== | ||
- | * daten! big! für deepest cyber! | + | |
+ | * daten! big! für deepest cyber! | ||
+ | * ASR | ||
+ | * https:// | ||
+ | * https:// | ||
==== HW ==== | ==== HW ==== | ||
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* portable power (printer needs a lot of power) | * portable power (printer needs a lot of power) | ||
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