fuyuxiang 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
| 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 |
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