Project Info
This project did not submit a demo video on Devpost.
Problem Statement Spoken language barriers do more than obstruct communication; they hinder the deep, emotional connections that bind us and limit opportunities in our increasingly global society. We've heard countless stories of individuals struggling to communicate with loved ones or feeling isolated in new environments due to language barriers: many grapple with a fear of judgment, making language acquisition incredibly difficult. People should be able to learn languages in a way that feels supportive, engaging, and tailored to their unique needs. The power of speech in breaking down barriers and forging connections in everyday life cannot be overstated. Our solution? Chime. As a group of Stanford students who experienced the difficulties of language learning through our own or our loved one's experiences, we wanted to make language learning more accessible for those who need it the most. About Chime Chime is an AI-driven conversational engine capable of adapting to individual learning styles and progress. Supports 56 languages Web & mobile app, with watchOS companion app Apple Watch “Chime-in” notifications for habit formation Integrates voice recognition, TTS, and AI LLMs Learning and takeaways Embarking on this project, we delved into the complexities of language acquisition, cognitive psychology, and AI technology. Through a combination of voice recognition and multi-model machine learning systems, we've created personalized learning paths and subtle feedback mechanisms to encourage fun and explorative conversations. Informed by our personal experiences and user interviews, we also developed interactive real-world role-play situations where users can practice and broaden their vocabularies. The journey of creating Chime has been challenging, yet incredible, and we can't wait to share this product with the people we've made it for! As we continue to grow and evolve Chime, our mission remains the same: to empower individuals to connect, communicate, and thrive in a multilingual world.
About Chime
Chime is an AI-driven conversational engine capable of adapting to individual learning styles and progress.
- Supports 6 languages
- For web & mobile Apple Watch “Chime-in” notifications for habit formation Integrates voice recognition, TTS, and AI LLMs
See devpost submission: https://devpost.com/software/chime-app
Demo Video
- Web/Mobile app: https://www.youtube.com/watch?v=d3ofPSFx7o4
- WatchOS app: https://www.youtube.com/watch?v=DSrn5Vp0aeI
Build instructions
To run the WatchOS companion app in Simulator: cd into chimeWatch_app, then open ChimeWatch.xcodeproj in XCode. Build the project for Apple Watch Series 9. To run the Web/iOS app in Simulator: cd into chime_app, run flutter get, then run build and debug from main.dart.
Analysis
View
Metric
- 1
- 1
Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.
Technology
- CIn code
- C++In code
- DartIn code
- HTMLIn code
- KotlinIn code
- SwiftIn code
- OpenAIClaimed
- PythonClaimed
6 of 8 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.
AI coding agents
No AI coding agent signals were found in this repository.
Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.
Codebase size
Source size
106 KB
Source files
52
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
kevintran-git/TreeHacks2024-Chime
157 files · 1.2 MB · @ f02af2c
Structure
Interface
14 files · 9%Screens, components and styles rendered to the user.
Application logic
78 files · 50%Domain rules, services and shared utilities.
+2 more
Supporting
Layers are inferred from where files sit in the tree, not from reading the code. A project that names its directories unconventionally will read oddly here — open the file browser to check anything the diagram implies.
Languages
- Dart61%
- C++17%
- C6%
- YAML5%
- XML5%
- Swift2%
- Other (3)3%
Share of indexed source by file size. Binary and vendored files are excluded.
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