بنقرة واحدة
voice-note
Convert voice messages to text (STT) and text to voice (TTS). Supports Whisper local model and Edge-TTS.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Convert voice messages to text (STT) and text to voice (TTS). Supports Whisper local model and Edge-TTS.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
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| name | voice-note |
| description | Convert voice messages to text (STT) and text to voice (TTS). Supports Whisper local model and Edge-TTS. |
| version | 1.0.0 |
| metadata | {"echo":{"tags":["Voice","STT","TTS","Whisper","Audio","Media"]}} |
Speech-to-Text (STT) and Text-to-Speech (TTS) capabilities.
from openai import OpenAI
client = OpenAI()
with open("audio.ogg", "rb") as f:
transcript = client.audio.transcriptions.create(model="whisper-1", file=f)
print(transcript.text)
pip install faster-whisper
from faster_whisper import WhisperModel
model = WhisperModel("base", compute_type="int8") # tiny/base/small/medium/large-v3
segments, info = model.transcribe("audio.ogg", language="zh")
text = " ".join(s.text for s in segments)
print(f"[{info.language}] {text}")
pip install edge-tts
# CLI
edge-tts --voice zh-CN-XiaoxiaoNeural --text "你好世界" --write-media output.mp3
# List voices
edge-tts --list-voices | grep zh-CN
import edge_tts, asyncio
async def speak(text, voice="zh-CN-XiaoxiaoNeural", output="output.mp3"):
communicate = edge_tts.Communicate(text, voice)
await communicate.save(output)
asyncio.run(speak("今天天气不错,适合出门"))
| Voice | Style |
|---|---|
| zh-CN-XiaoxiaoNeural | 女声,活泼自然 |
| zh-CN-YunxiNeural | 男声,温和 |
| zh-CN-YunyangNeural | 男声,新闻播报 |
| zh-CN-XiaoyiNeural | 女声,温柔 |
python3 scripts/voice_process.py transcribe audio.ogg --model base --language zh --output transcript.txt
python3 scripts/voice_process.py summarize meeting.mp3 --model small
Note: TTS (speak/voices) is in the separate tts-voice skill.
ffmpeg -i input.ogg output.mp3