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BETA TEST PLAN – TEMPLATE

1. Project context

HuRI is a research-driven platform that has the objective to act as a universal middleware for speech and movement for any various physical or digital human embodiments. The focus on our part is to have embodiments as human as possible, regarding the emotion aspect, and try to go beyond the uncanny valley. The goal is to create a modular ecosystem where any combination of AI can control any robot or any virtual avatar. The project focuses on a highly stable architecture, scalable cloud deployment, and innovative emotional expression through motion and voice.

2. User role

Role Name Description
Library Maintainer Manages the core Python package, handles versioning, and ensures the stability of the base classes and API.
Module Developer Uses the library to build and package custom plugins or specialized modules for specific use cases.
DevOps Engineer Handles the containerization, orchestration, and distribution of the library across different network nodes or edge devices.
Client User of the library

3. Feature table

Feature ID User role Feature name Short description
F1 Everyone Create Module The lib allows to create a module and use it.
F2 Everyone Config file Config file to launch different module combinations.
F3 Everyone Parallelism HuRI can run on 1 to N machines, to split computation and balance payload.
F4 Everyone Multi-client HuRI can be used on 1 to N robots with separated discussions.
F5 Everyone Module - MIC User can talk to HuRI through microphone.
F6 Everyone Module - SPK HuRI can talk to User through speakers.
F7 Everyone Module - STT HuRI can transcribe speech into text.
F8 Everyone Module - INP User can chat to HuRI through terminal.
F9 Everyone Module - OUT HuRI can chat to User through terminal.
F10 Everyone Module - MOD HuRI has 3 modes: Discussion, Inserting context & Inserting information. User can switch between modes.
F11 Everyone Module - TTS HuRI can generate speech with text. Generate audio.
F12 Everyone Module - MOV HuRI can generate body movement by putting points in space
F13 Everyone Module - RAG HuRI can retrieve text from files, saved texts, old conversations, etc.
F14 Everyone Module - LLM HuRI can generate text from a given context
F15 Everyone Module - TAN User speech text will be analysed to understand their emotion.
F16 Everyone Module - EIN Analysed emotion is mixed with the context.
F17 Everyone Module - AMM HuRI will store and manage an artificial memory

4. Success Criteria

Feature ID Key success criteria Indicator/metric Result
F1 Creating various Modules. 20 attempts -- expected 100% Achieved (/20)
F2 Launching different scenarios with different config files. 5 files -- expected 100% Achieved (/5)
F3 - F4 Running 1 or several modules on 1 or several machines. All modules running on 1 machine. All modules running on different machines. Several modules running on several machines. Scenario achieved (/3)
F5 Using a microphone and being recorded. 10 messages recorded over 3 different devices -- expected 100% Files recorded (/30)
F6 Emitting sound through speakers. 10 audio files played on 3 different devices -- expected 100% Files heard (/30)
F7 Transcribing speech to text correctly. 20 spoken phrases -- expected 80% accuracy Phrases correct (/20)
F8 Sending text input via terminal. 10 text inputs -- expected 100% Inputs received from another module (/10)
F9 Receiving text output via terminal. 10 text outputs from another module -- expected 100% Outputs displayed (/10)
F10 Switching between the 3 modes (Discussion, Context, Info). Switch 10 times -- expected 100% success Switches successful (/10)
F11 Generating audio file from text input. 10 text inputs -- expected 100% generation Files generated (/10)
F12 Making human movement human feeling* -- expected 60% Human feedback in %
F13 Retrieving context from a saved file. 10 queries on saved text -- expected 100% retrieval Relevant text found (/10)
F14 Generating a response from a context. 10 prompts -- expected 100% answer generation Answers generated (/10)
F15 Understanding of emotions from the interlocutor. 10 emotion texts to analyse -- expected 60% Emotion analysed (/10)
F16 Understanding of the global emotion of the interlocutor 10 emotional contexts to analyse -- expected 60% 10 emotional contexts (/10)
F17 Saving of important information with an update that removes information when they are old / not relevant anymore / not remembered 10 pieces of information to save and treat over time -- expected 60% 10 prompts to save and treat (/10)

*Experiments will be conducted on several people and a Godspeed-based questionnaire will evaluate the human feeling