speech-to-text

inference-sh/skills · updated Apr 8, 2026

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$npx skills add https://github.com/inference-sh/skills --skill speech-to-text
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summary

Transcribe audio to text via inference.sh CLI.

skill.md

Speech-to-Text

Transcribe audio to text via inference.sh CLI.

Speech-to-Text

Quick Start

Requires inference.sh CLI (infsh). Install instructions

infsh login

infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://audio.mp3"}'

Available Models

Model App ID Best For
ElevenLabs Scribe v2 elevenlabs/stt 98%+ accuracy, diarization, 90+ languages
Fast Whisper V3 infsh/fast-whisper-large-v3 Fast transcription
Whisper V3 Large infsh/whisper-v3-large Highest accuracy

Examples

Basic Transcription

infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://meeting.mp3"}'

With Timestamps

infsh app sample infsh/fast-whisper-large-v3 --save input.json

# {
#   "audio_url": "https://podcast.mp3",
#   "timestamps": true
# }

infsh app run infsh/fast-whisper-large-v3 --input input.json

Translation (to English)

infsh app run infsh/whisper-v3-large --input '{
  "audio_url": "https://french-audio.mp3",
  "task": "translate"
}'

From Video

# Extract audio from video first
infsh app run infsh/video-audio-extractor --input '{"video_url": "https://video.mp4"}' > audio.json

# Transcribe the extracted audio
infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "<audio-url>"}'

Workflow: Video Subtitles

# 1. Transcribe video audio
infsh app run infsh/fast-whisper-large-v3 --input '{
  "audio_url": "https://video.mp4",
  "timestamps": true
}' > transcript.json

# 2. Use transcript for captions
infsh app run infsh/caption-videos --input '{
  "video_url": "https://video.mp4",
  "captions": "<transcript-from-step-1>"
}'

Supported Languages

Whisper supports 99+ languages including: English, Spanish, French, German, Italian, Portuguese, Chinese, Japanese, Korean, Arabic, Hindi, Russian, and many more.

Use Cases

  • Meetings: Transcribe recordings
  • Podcasts: Generate transcripts
  • Subtitles: Create captions for videos
  • Voice Notes: Convert to searchable text
  • Interviews: Transcription for research
  • Accessibility: Make audio content accessible

Output Format

Returns JSON with:

  • text: Full transcription
  • segments: Timestamped segments (if requested)
  • language: Detected language

Related Skills

# ElevenLabs STT (98%+ accuracy, diarization)
npx skills add inference-sh/skills@elevenlabs-stt

# ElevenLabs TTS (reverse direction)
npx skills add inference-sh/skills@elevenlabs-tts

# Full platform skill (all 150+ apps)
npx skills add inference-sh/skills@infsh-cli

# Text-to-speech (reverse direction)
npx skills add inference-sh/skills@text-to-speech

# Video generation (add captions)
npx skills add inference-sh/skills@ai-video-generation

# AI avatars (lipsync with transcripts)
npx skills add inference-sh/skills@ai-avatar-video

Browse all audio apps: infsh app list --category audio

Documentation

how to use speech-to-text

How to use speech-to-text on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add speech-to-text
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/inference-sh/skills --skill speech-to-text

The skills CLI fetches speech-to-text from GitHub repository inference-sh/skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/speech-to-text

Reload or restart Cursor to activate speech-to-text. Access the skill through slash commands (e.g., /speech-to-text) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

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general reviews

Ratings

4.825 reviews
  • Naina Okafor· Dec 24, 2024

    I recommend speech-to-text for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Ganesh Mohane· Dec 16, 2024

    Useful defaults in speech-to-text — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Amina Zhang· Dec 4, 2024

    Solid pick for teams standardizing on skills: speech-to-text is focused, and the summary matches what you get after install.

  • Alexander Abebe· Nov 23, 2024

    We added speech-to-text from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Alexander Farah· Oct 14, 2024

    speech-to-text fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Isabella Martin· Sep 21, 2024

    Solid pick for teams standardizing on skills: speech-to-text is focused, and the summary matches what you get after install.

  • Rahul Santra· Sep 13, 2024

    speech-to-text has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Aarav Zhang· Aug 24, 2024

    Keeps context tight: speech-to-text is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Isabella Taylor· Aug 12, 2024

    speech-to-text has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Pratham Ware· Aug 4, 2024

    Solid pick for teams standardizing on skills: speech-to-text is focused, and the summary matches what you get after install.

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