Week 1 #
Project description #
Project name: VoiceDiary
Code repository: link
VoiceDiary is an AI-powered voice journaling tool that analyzes tone, emotion, and key themes in spoken entries. It generates personalized emotional insights and well-being suggestions based on recorded reflections.
Team #
Team member | Telegram alias | Innopolis Email | Responcibilities |
---|---|---|---|
Dziyana Melnikava | @meldilen24 | dz.melnikava@innopolis.university | PM, Frontend |
Anastasia Kuchumova | @n_rngk | a.kuchumova@innopolis.university | Frontend, UX/UI |
Dzhamilia Fatkullina | @jam11a | d.fatkullina@innopolis.university | ML |
Elina Kuzmichyova | @lin_anile | e.kuzmichyova@innopolis.university | ML |
Olesia Novoselova | @doiwannaknoww8 | o.novoselova@innopolis.university | Backend |
Danil Davydyan | @chocop | d.davydyan@innopolis.university | Backend |
Brainstorming #
Ideas during brainstorming #
| Rank | Idea | | 1 | An AI-based voice journaling platform that processes spoken reflections to detect emotional tone, mood trends, and core topics, offering personalized mental well-being feedback. | | 2 | A self-growth tracker where users build and evolve virtual āselvesā representing different aspects of personality. | | 3 | A sleep-integrated dream and emotion journal that analyzes voice-recorded dreams and detects subconscious emotional trends. |
Problem validation #
1. VoiceDiary
Problem: People often struggle to identify and understand their emotional patterns, lack time or motivation for traditional journaling, and find it hard to reflect consistently.
Validation:
- Voice is perceived as a more natural and less effort-intensive method of self-expression in self-reflection contexts.
2. PersonaPulse
Problem: Many people feel disconnected from different parts of their personality (e.g., professional vs emotional self) and lack structured tools to develop personal traits in a holistic and engaging way.
Validation:
- Behavioral patterns suggest that people engage more when self-development is approached playfully or symbolically rather than abstractly.
3. Sleep-Sleep
Problem: Dreams are a rich source of emotional insight, but most people forget them quickly or lack a structured way to reflect on their subconscious thoughts.
Validation:
- Cognitive psychology suggests that reflecting on dream content can increase awareness of unresolved emotional issues.
Basic Requirements #
Target Users and Their Primary Needs #
Reflective Individuals: People interested in understanding themselves better, journaling, or mental wellness
- Need: A natural, non-intrusive way to reflect emotionally
Busy Individuals: People with limited time for self-reflection or therapy
- Need: A low-effort tool to track emotions and stress without interrupting routine
User Stories #
- As a user, I want to speak freely into the app so I can reflect without needing to write or plan.
- As a user, I want the experience to require minimal effort so I can use it even on busy or stressful days.
- As a user, I want the app to identify patterns in my mood and emotions over time so I can understand my mental state (statistics).
- As a user, I want the system to recognize tone and key themes in what I say so I can gain deeper self-insights.
- As a user, I want to receive recommendations so I can take small steps toward emotional well-being.
- As a user, I want the app to feel like a personal, private space so I can be honest and unfiltered in my entries.
Initial Scope (MVP) #
IN Scope (W1āW3) | OUT (Post-MVP) |
---|---|
Basic homepage with embedded calendar | Authentication + Enhanced homepage with achievements |
Integration with 1 emotion recognition model | Voice record analysis + recommendations |
No statistics | Emotion statistics (weekly/monthly/yearly) |
Tech Stack #
Choice | Justification | |
---|---|---|
Frontend | React | For building a responsive, modern web interface with reusable components and efficient state management. |
Backend | Golang | High performance, concurrency support, and fast API response times; suitable for real-time web services. |
ML API | Python | Extensive machine learning libraries and seamless integration with pretrained models. |
ML Models | Whisper (by OpenAI), Emotion_Recognition_From_Speech, xlsr-wav2vec-speech-emotion-recognition | Open-source, speech-focused models with high accuracy; suitable for emotion detection from voice; will be tested and selected based on performance. |
LLaMA | To generate contextual emotional feedback and personalized recommendations based on analysis. | |
Database | PostgreSQL | Reliable relational database with strong consistency guarantees and support for structured data (e.g. logs, users, entries). |
Auth | OAuth | Standard and secure method for third-party authentication, reduces password handling and improves UX. |
Infra | Docker + Docker Compose | Ensures consistent development and production environments, simplifies deployment. |
GitHub Actions (CI/CD) | Enables continuous integration, testing, and deployment with minimal manual effort. |
Collective commitments #
Met with the team, Discussed our project visions, Finalized the system architecture and technology stack after thorough discussion of all ideas.
Individual commitments #
Confirmation of the codeās operability #
We confirm that the code in the main branch:
- [ā] In working condition.
- [ā] Run via docker-compose (or another alternative described in the
README.md
).