voice-note

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]

Voice Note

Speech-to-Text (STT) and Text-to-Speech (TTS) capabilities.

Speech → Text

Option A: OpenAI Whisper API (cloud)

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)

Option B: faster-whisper (local, no API key)

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}")

Text → Speech

Edge-TTS (free, excellent Chinese voices)

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"))

Chinese Voice Options

Script

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.

Audio Format Notes

• Input formats: ogg, mp3, wav, m4a, webm (Whisper accepts most)
• Output: mp3 (Edge-TTS default)
• Convert: ffmpeg -i input.ogg output.mp3