Qwen Voice (ASR + TTS)

Use the bundled scripts. Configure DASHSCOPE_API_KEY in one of:

• ~/.config/qwen-voice/.env (recommended)
• <repo>/.qwen-voice/.env (dev/testing)

ASR (speech → text)

Non-timestamp (default)

python3 skills/qwen-voice/scripts/qwen_asr.py --in /path/to/audio.ogg

With timestamps (chunk-based)

python3 skills/qwen-voice/scripts/qwen_asr.py --in /path/to/audio.ogg --timestamps --chunk-sec 3

Notes:

• Timestamps are generated by fixed-length chunking (not word-level alignment).
• Input audio is converted to mono 16kHz WAV before sending.

TTS (text → speech)

Preset voice (default: Cherry)

python3 skills/qwen-voice/scripts/qwen_tts.py --text '你好，我是 Pi。' --voice Cherry --out /tmp/out.ogg

Clone voice (create once, reuse)

1. Create a voice profile from a sample audio:

python3 skills/qwen-voice/scripts/qwen_voice_clone.py --in ./voice_sample.ogg --name george --out work/qwen-voice/george.voice.json

2. Use the cloned voice to synthesize:

python3 skills/qwen-voice/scripts/qwen_tts.py --text '你好，我是 George。' --voice-profile work/qwen-voice/george.voice.json --out /tmp/out.ogg

Notes:

• .ogg output is Opus, suitable for Telegram voice messages.
• Voice cloning uses DashScope customization endpoint + Qwen realtime TTS model.
• Scripts use a local venv at work/venv-dashscope (auto-created on first run).

Typical chat workflow

• When user sends voice message/audio: run ASR and reply with the transcribed text.
• When user explicitly asks for voice reply: run TTS and send the generated .ogg as a voice note.