Skill: okaris/speech-to-text (version 0.1.5)

--- name: speech-to-text description: "Transcribe audio to text with Whisper models via inference.sh CLI. Models: Fast Whisper Large V3, Whisper V3 Large. Capabilities: transcription, translation, multi-language, timestamps. Use for: meeting transcription, subtitles, podcast transcripts, voice notes. Triggers: speech to text, transcription, whisper, audio to text, transcribe audio, voice to text, stt, automatic transcription, subtitles generation, transcribe meeting, audio transcription, whisper ai" allowed-tools: Bash(infsh *) --- # Speech-to-Text Transcribe audio to text via [inference.sh](https://inference.sh) CLI. ![Speech-to-Text](https://cloud.inference.sh/u/4mg21r6ta37mpaz6ktzwtt8krr/01jz025e88nkvw55at1rqtj5t8.png) ## Quick Start ```bash curl -fsSL https://cli.inference.sh | sh && infsh login infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://audio.mp3"}' ``` > **Install note:** The [install script](https://cli.inference.sh) only detects your OS/architecture, downloads the matching binary from `dist.inference.sh`, and verifies its SHA-256 checksum. No elevated permissions or background processes. [Manual install & verification](https://dist.inference.sh/cli/checksums.txt) available. ## Available Models | Model | App ID | Best For | |-------|--------|----------| | Fast Whisper V3 | `infsh/fast-whisper-large-v3` | Fast transcription | | Whisper V3 Large | `infsh/whisper-v3-large` | Highest accuracy | ## Examples ### Basic Transcription ```bash infsh app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://meeting.mp3"}' ``` ### With Timestamps ```bash 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) ```bash infsh app run infsh/whisper-v3-large --input '{ "audio_url": "https://french-audio.mp3", "task": "translate" }' ``` ### From Video ```bash # 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 ```bash # 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 ```bash # Full platform skill (all 150+ apps) npx skills add inference-sh/skills@inference-sh # 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 - [Running Apps](https://inference.sh/docs/apps/running) - How to run apps via CLI - [Audio Transcription Example](https://inference.sh/docs/examples/audio-transcription) - Complete transcription guide - [Apps Overview](https://inference.sh/docs/apps/overview) - Understanding the app ecosystem


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)