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Found 88 Skills
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
Transcribe audio to text using ElevenLabs Scribe v2. Use when converting audio/video to text, generating subtitles, transcribing meetings, or processing spoken content.
Implement the Syncfusion React SpeechToText component. Use this skill to convert speech to text, manage microphone input, control listening states, process speech events, customize UI, support accessible voice-enabled forms, and handle globalization and security in React applications.
Implement the Syncfusion Angular SpeechToText component. Use this skill for real-time speech-to-text conversion with text transcripts, custom button appearance and tooltips, recognition event handling, multiple language support with localization and RTL, error handling, and security best practices for microphone access and data transmission.
Expert skill for implementing speech-to-text with Faster Whisper. Covers audio processing, transcription optimization, privacy protection, and secure handling of voice data for JARVIS voice assistant.
Implement the Syncfusion ASP.NET Core SpeechToText control for converting spoken words to text using Web Speech API. Use this skill when implementing speech recognition with Razor Tag Helpers, converting voice to text in ASP.NET Core applications, handling microphone input, processing speech events, customizing button appearance, managing listening states, or building accessible voice-enabled forms. Covers setup, speech recognition features, Razor Tag Helper syntax, events, methods, globalization, and security.
Implement speech-to-text voice input in Blazor applications using Syncfusion SpeechToText component. ALWAYS use this when users need voice input, speech recognition, audio transcription, or implementing the SpeechToText component in Blazor. Trigger for Syncfusion.Blazor.Inputs, microphone input, voice-to-text conversion, language support, transcript binding, listening states, error handling, browser speech API, or any speech recognition requirements.
Transcribe audio to text using Sarvam AI's Saaras model. Handles speech recognition, transcription, and voice interfaces for 23 Indian languages. Supports 5 output modes, auto language detection, WebSocket streaming, and batch diarization. Use when converting speech to text or building voice-enabled apps.
Use this skill whenever the user wants to transcribe audio to text, convert speech to text, or get a transcript from an audio or video file. Triggers include: any mention of 'transcribe', 'transcription', 'speech to text', 'STT', 'convert audio to text', 'what does this audio say', 'get transcript', 'subtitle generation', or requests to extract spoken words from a file. Also use when the user wants speaker identification from audio, timestamps for captions, or multilingual transcription.
Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization. Triggers: "transcription", "speech to text", "Azure AI Transcription", "TranscriptionClient".
Local speech-to-text via Handy app (push-to-talk) and NeMo CLI scripts. Parakeet V3: 25 languages, auto-detection, ~30x realtime on M4 Max, 6% WER. This skill should be used when transcribing audio files or dictating voice input.
Use local FunASR service to transcribe audio or video files into timestamped Markdown files, supporting common formats such as mp4, mov, mp3, wav, m4a, etc. This skill should be used when users need speech-to-text conversion, meeting minutes, video subtitles, or podcast transcription.