XTTS Integration for Multilingual Speech Synthesis

XTTS Integration for Multilingual Speech Synthesis XTTS v2 (Coqui) is a multilingual TTS model with zero-shot voice cloning from 3–6 seconds of reference audio. Supports 17 languages, including Russian. The main advantage: one voice synthesized in multiple languages. ### Supported languages: en, es, fr, de, it, pt, pl, tr, ru, nl, cs, ar, zh-cn, hu, ko, ja, hi ### Installation

pip install TTS
python -c "from TTS.api import TTS; TTS('tts_models/multilingual/multi-dataset/xtts_v2')"
```### Cross-lingual synthesis```python
from TTS.api import TTS

tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to("cuda")

# Один референсный голос → несколько языков
reference_voice = "speaker_sample.wav"

languages = {
    "ru": "Добро пожаловать в нашу компанию!",
    "en": "Welcome to our company!",
    "de": "Willkommen in unserem Unternehmen!",
    "fr": "Bienvenue dans notre entreprise!"
}

for lang, text in languages.items():
    tts.tts_to_file(
        text=text,
        speaker_wav=reference_voice,
        language=lang,
        file_path=f"output_{lang}.wav"
    )
```### Reference Audio Requirements - Length: 3–30 seconds (optimally 6–12 seconds) - Quality: 22 kHz+, no noise or reverberation - Content: clear speech of one speaker without music ### Optimized for production```python
# Предкомпьютим gpt_cond_latent для частого референсного голоса
from TTS.tts.configs.xtts_config import XttsConfig
from TTS.tts.models.xtts import Xtts

config = XttsConfig()
config.load_json("/path/to/config.json")
model = Xtts.init_from_config(config)
model.load_checkpoint(config, checkpoint_dir="/path/to/model/")
model.cuda()

gpt_cond_latent, speaker_embedding = model.get_conditioning_latents(
    audio_path=["reference.wav"]
)
# Кэшируем latents — не пересчитываем при каждом запросе
```Speed: XTTS v2 on RTX 3090 — ~1.5–2x realtime (generates 1 second of audio in 0.5–0.7 seconds). Timeframe: integration — 2–3 days. With latency optimization — 1 week.