Review Your Feedback
I just made a recording of my voice. Now what?
After you make (or import) a recording, Speeko gives you feedback on your speaking style. You’ll learn your strengths and find ways to speak more confidently.
How do I interpret the feedback?
- Read the 2-sentence summary at the top of your feedback report.
This highlights your top strength and one area that could be holding you back.
- Scan the overview of your performance.
Below the summary, you’ll find your performance across 6 metrics: Pace, Eloquence, Pausing, Intonation, Articulation, and Word Choice. If you see
next to a metric, pay attention to that as an area to work on. - Tap each metric for in-depth feedback.
Under each metric, you’ll find a graph that helps you pinpoint specific areas of your recording to listen back to. For Eloquence and Word Choice, tap “See in Transcript” to review where you used specific words and phrases.
Listen to your recording as you review the feedback. You’ll quickly become comfortable with listening to your own voice and identifying areas you want to improve!
Which area of my speaking style do I need to improve the most?
At the bottom of your feedback report is a recommended exercise based on what Speeko suggests as your top priority.
The next time you record yourself speaking, focus on this one area. It’s easier to focus on one area rather than multiple areas at the same time!
How do I assess my progress over time?
Go to the “Progress” tab of the app to review your performance over multiple recordings.
As you review your recordings, ask yourself these questions:
- Is the quality of my speaking style improving?
Listen to your recordings, and note any changes in your speaking style. Does your voice sound more confident? Clearer? More engaging?
- Am I becoming more consistent?
Check whether your metrics are similar between recordings.
What is Speeko’s A.I. based on?
Our algorithms are based on published studies by academic experts of what English-speaking audiences consider as effective communication.
We’re committed to making our A.I. to be as objective and unbiased as possible, so we train our A.I. on a balanced dataset with respect to gender and cultural background.