Fluently is an AI-powered speaking coach designed to enhance English language skills through personalized feedback after online calls. It aims to boost users' confidence in speaking English by providing tailored insights and practice opportunities.
Fluently is an AI-powered speaking coach designed to enhance English language skills through personalized feedback after online calls. It aims to boost users' confidence in speaking English by providing tailored insights and practice opportunities.
Fluently analyzes speech patterns during real-life calls, offering customized feedback to help users identify and correct common mistakes in spoken English.
The app provides detailed insights on pronunciation, helping users refine their speaking skills based on their actual conversations.
Users can monitor their improvement over time through:
Fluently operates seamlessly without requiring complex setup, allowing users to focus solely on improving their English skills.
The app offers round-the-clock opportunities for speaking practice, providing feedback to support continuous improvement.
Fluently's simple usage process:
| Offer | Details |
|---|---|
| Free Trial | Available for new users |
| Subscription | Affordable plans post-trial |
Fluently activates automatically during English conversations, analyzing speech patterns and providing personalized feedback after each call to help improve speaking skills.
No, Fluently prioritizes user privacy and does not use personal data for training purposes.
Yes, users can delete their accounts at any time, which also removes all associated data.
Fluently employs industry-standard security protocols, including transit encryption and local storage & privacy control, ensuring maximum security for users.
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Identifying People Expressions in Google Meets Calls This is a complex task with several challenges: * Technical Limitations: Google Meets doesn't currently offer an API to directly access facial expressions of participants. * Privacy Concerns: Analyzing facial expressions raises significant privacy issues. Users should have control over whether their expressions are being tracked and used. * Accuracy: Even with access to facial data, accurately interpreting expressions can be difficult due to variations in lighting, angles, and individual differences. Possible Approaches (with limitations): * User-Submitted Data: Participants could manually indicate their emotions during the call, which could be collected and analyzed. This relies on user honesty and may not capture subtle expressions. * Third-Party Tools: Some external tools might analyze video feeds and attempt to detect expressions. However, their accuracy and privacy practices should be carefully evaluated. * Future Developments: Google or other companies might develop features that allow for more ethical and accurate expression analysis in the future. It's important to remember that facial expressions are just one aspect of communication, and relying solely on them can be misleading.