Transcribe audio files with OpenAI Whisper and synthesize speech from text.
npx skills add https://github.com/kaivyy/kabot --skill voice-skill
Please help me install this Agent Skill. Skill: Voice Skill Source: https://github.com/kaivyy/kabot/tree/main/kabot/skills/voice Command: npx skills add https://github.com/kaivyy/kabot --skill voice-skill
This skill enables seamless voice interaction by converting spoken words into text and generating spoken audio from text.
Use the voice skill to transcribe the audio file named 'meeting_recording.mp3'.
High-intent search queries and answers about installing and using this skill.
To transcribe an audio file to text, the Voice Skill uses OpenAI's Whisper model to convert spoken audio into written text. You simply provide the audio file, and the skill processes the speech-to-text transcription automatically.
Yes, you can convert text to speech using OpenAI's TTS models to generate natural-sounding spoken audio. This text-to-speech synthesis allows you to create spoken responses from written content.
Yes, an OpenAI dependency is required because the skill relies on OpenAI's Whisper for transcription and TTS models for speech generation. You must configure your OpenAI access before using these audio features.
The best way to process voice commands and dictate audio notes is using a skill that handles both speech-to-text transcription and text-to-speech synthesis. This enables seamless voice interaction by converting spoken words into text and generating spoken audio.
The skill supports speech-to-text transcription of standard audio files like meeting recordings. It uses OpenAI's Whisper model to process the audio, though specific compatible file extensions depend on the Whisper API's current capabilities.
cogpyTranscribe audio files into text using the OpenAI Audio Transcriptions API.
cafe3310Process long speech transcripts with segmented editing and resumable operations.
wulaosijiConvert media formats and transcribe audio using FFmpeg and Whisper.
guoqiaoTranscribe audio files locally using MLX on Apple Silicon.
