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Voice Feedback Coach: Filler & Pause Analysis

Daily 1-minute speaking drills that help non-native speakers cut fillers and awkward pauses

Problem
Many people fear public speaking and lack the constant, specific feedback a debate team provides. Voice AI still relies on transcripts to judge emotion—'I'm frustrated with your service' reads the same whether calm or angry—so users get no real feedback on fillers, pauses, or tone.
Solution
A voice-first practice tool: push a 1-minute speaking prompt daily, use on-device audio analysis to detect filler words, pause frequency, pace, and emotional tone, and surface a visual report with improvement tips—no transcript dependency.
Users
Professionals improving speaking skills, non-native English speakers, founders preparing pitches or interviews
MVP
Daily 1-minute prompt delivery; record and locally analyze fillers, pauses, pace; generate visual report and tips; view historical trends; analyze without uploading audio
Revenue
Free 1 drill/day; $6.9/mo subscription for unlimited drills, trends, and personalized plans; team plan per seat
Why now
On-device speech and emotion models are lightweight enough, remote meetings and video interviews are standard, and existing tools stop at transcription—leaving a gap for audio-native feedback

Source discussions · 3

  1. Hacker NewsWhy the ways of interactions, social and devices, haven't changed yet1↑ 0
  2. Hacker NewsShow HN: SpeakUp – iOS app for feedback on your speaking (fillers, pauses, etc.)1↑ 0
  3. Hacker NewsShow HN: SpectroMood, speech emotion detection with a decision model1↑ 0
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