Turn speeches
~ 안으로 tone, text, action.

A different approach to speech analysis.

Speech analysis is the process of turning a recording of spoken delivery into insight: what the speaker said, how the room reacted, and where the message actually landed. Researchers, coaches, and communications teams have used it for years to sharpen speeches before politicians, executives, and conference speakers ever say them out loud.

Why a transcript alone misses the speech

Most speech review still stops at the words. A rehearsal gets recorded, someone skims the transcript for typos, and the note back is generic: good energy, trim the middle. What the transcript cannot show is the six seconds of silence after a joke that did not land, the pace that doubled when the speaker got nervous at slide 4, or the flat tone that crept in exactly when the numbers slide went up. Speeches are read off-screen as much as they are said out loud, and a text-only review misses both halves.

How Speak AI reads a speech

Speak AI transcribes the recording in your language, with 100+ supported, and then analyzes the delivery itself: the tone, emotion, and energy of the speaker, second by second, alongside the visuals on screen, so a dip in energy is tied to the exact slide, cue, or line that caused it. Names, topics, and audience reactions are extracted into structured fields your systems can use, and the same recordings are queryable from Claude, ChatGPT, and Gemini through the MCP server, so a coach or comms lead can ask a question instead of scrubbing a timeline.

What teams ask their speeches

• “Where does the speaker’s energy drop, and which slide was on screen when it happened?”
• “What is the overall tone of this speech, and does it shift by section?”
• “Which lines got the strongest audience reaction across every rehearsal?”
• “Compare this speech against last quarter’s version for pacing and filler words.”
• “Summarize the key themes and any moments the message contradicted itself.”

From one rehearsal to a trend line

The result is feedback that points at a moment, not a mood. Coaches see exactly where a client rushes, dashboards you can customize and white-label track energy, pacing, and audience response across every rehearsal, and a speech gets measured against its own last version instead of a gut feeling. A legal intelligence firm ran a similar volume of recorded material through this workflow and processed 5,100+ hours and saved $700K, without adding headcount. And because a speech is rarely reviewed alone, the same engine scores calls and meetings on the same criteria, connecting rehearsal review to full coaching across every conversation your team has.