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ltts

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Quick CLI for local text-to-speech using Qwen3-TTS or Kokoro TTS.

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- - publish.yml
- __init__.py
- backends.py
- cli.py
- kokoro_backend.py
- qwen_backend.py
- release.sh
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Quick CLI for local text-to-speech with two backends: [Qwen3-TTS](https://github.com/QwenLM/Qwen3-TTS) (default) and [Kokoro TTS](https://huggingface.co/hexgrad/Kokoro-82M).

## Install

Recommended (fast, reproducible):

```bash
uv tool install ltts
```

Run without installing:

```bash
uvx ltts "hello world" --say
```

With pip:

```bash
pip install ltts
```

### NVIDIA GPU (Optional)

For faster inference on NVIDIA GPUs:

```bash
pip install 'ltts[cuda]'
```

## Usage

```bash
# Generate speech (saves to output.mp3 by default)
ltts "Hello, world!"

# Play through speakers
ltts "Hello, world!" --say

# Save to specific file
ltts "Hello, world!" -o speech.wav

# Read from stdin
echo "Hello from pipe" | ltts --say
cat article.txt | ltts -o article.mp3
```

## Backends

### Qwen3-TTS (default)

Higher quality with voice cloning and emotional control. Supports 10 languages.

```bash
# Preset voices
ltts "Hello, world!" -v Ryan --say       # English male (default)
ltts "Hello, world!" -v Aiden --say      # English male
ltts "你好世界" -v Vivian --say           # Chinese female
ltts "こんにちは" -v Ono_Anna --say       # Japanese female
ltts "안녕하세요" -v Sohee --say           # Korean female

# Voice cloning (3+ seconds of reference audio)
ltts "Hello in your voice" --ref-audio voice.wav --say
ltts "Hello" --ref-audio voice.wav --ref-text "transcript" --say

# Emotional control
ltts "I can't believe we won!" --instruct "speak with excitement" --say

# Smaller model for faster inference
ltts "Hello world" --model-size 0.6B --say
```

**Preset voices:** Ryan, Aiden (English), Vivian, Serena, Dylan, Eric, Uncle_Fu (Chinese), Ono_Anna (Japanese), Sohee (Korean)

**Languages:** en, zh, ja, ko, de, fr, es, pt, it, ru

### Kokoro TTS

Lightweight with 50+ voices. Supports streaming for faster time-to-first-audio.

```bash
# Use Kokoro backend
ltts "Hello world" -b kokoro -v af_heart --say
ltts "こんにちは" -b kokoro -v jf_alpha --say

# Stream chunks as generated (lower latency)
ltts "Hello world" -b kokoro --say --chunk
```

**Voices:** af_heart, af_alloy, af_bella, am_adam, am_michael (American), bf_alice, bf_emma, bm_daniel (British), jf_alpha, jm_kumo (Japanese), zf_xiaobei, zm_yunxi (Chinese), ef_dora, em_alex (Spanish), ff_siwis (French), and more.

Full voice list: https://huggingface.co/hexgrad/Kokoro-82M/blob/main/VOICES.md

## Options

```bash
# Device selection
ltts "Hello" -d cpu --say    # CPU (default)
ltts "Hello" -d cuda --say   # NVIDIA GPU
ltts "Hello" -d mps --say    # Apple Silicon

# Output formats
ltts "test" -o out.mp3       # MP3 (default)
ltts "test" -o out.wav       # WAV
ltts "test" -o out.ogg       # OGG
ltts "test" -o out.flac      # FLAC

# Language override
ltts "Bonjour" -l fr --say
```

## Notes

- First run downloads models to `~/.cache/huggingface/` (~3GB for Qwen 1.7B, ~330MB for Kokoro)
- Audio playback (`--say`) runs at 24 kHz
- On Linux, ensure PulseAudio/PipeWire is running for audio playback

## Development

```bash
uv sync
uv run ltts "hello world" --say
uv run ltts "hello world" -b kokoro -v af_heart --say
./scripts/release.sh
```