AI Communication Coach

Inspiration

The idea for Coach Aura began with a common feeling many of us share: that moment right before you have to speak up. Whether it's a critical job interview, a presentation at work, or simply trying to express yourself clearly in everyday conversations, there's often a quiet anxiety. We want to sound confident, articulate, and truly connect, but sometimes the right words just don't come, or we worry about how we're coming across. I was inspired by this universal need for better, more confident communication, and the desire to make personalized coaching accessible to everyone.

What it does

Building Coach Aura was a journey of learning and problem-solving. My goal was to create a tool that felt genuinely helpful, not just technical. I dove into understanding how conversational AI works, focusing on making the interaction smooth and natural. A key part of this learning was figuring out how to analyze spoken language effectively – not just transcribing words, but understanding common speaking habits like filler words or pacing issues.

How we built it

I built Coach Aura using Bolt.new, which was instrumental in bringing this vision to life quickly. Bolt allowed me to focus on the core user experience and the intelligence behind the coaching, handling much of the underlying code generation. For the interactive video aspect of Coach Aura, I integrated Tavus. Tavus provided the realistic video persona, making the coaching sessions feel more human and engaging than just a disembodied voice or text. The user's spoken input is captured through their microphone, transcribed using the browser's native speech-to-text capabilities, and then analyzed by the system to provide precise, actionable feedback.

Challenges we ran into

Of course, building a project like this came with its challenges. Getting the real-time feedback loop just right was a significant hurdle – ensuring that Coach Aura could listen, process, analyze, and then respond quickly and naturally, all while keeping the user engaged. Fine-tuning the grammar analysis and filler word detection to be consistently accurate and context-aware also required careful iteration. Another area that demanded persistence was integrating the visual feedback, such as eye-contact tracking, and ensuring it worked smoothly across different devices while respecting user privacy.

Accomplishments that we're proud of

The whole project is an accomplishment on its own

What we learned

While it's tempting to offer every possible data point, I found that focused, actionable feedback is more impactful. Learning to prioritize the most critical insights for the user's immediate improvement was key.

What's next for AI Communication Coach

I aim to develop features that allow Coach Aura to track a user's progress over time and suggest personalized exercises or areas of focus based on their unique communication patterns and goals.

Built With

• bolt.new
• netlify
• tavus