Voice Cloning with XTTS

write a guide on how to use https://huggingface.co/coqui/XTTS-v2 to clone a voice and to use it

Here’s a full guide on how to use **[Coqui XTTS v2](https://huggingface.co/coqui/XTTS-v2)** to **clone a voice** and **generate speech** using that voice. --- ## 🔊 What is XTTS-v2? **XTTS (Cross-lingual Text-to-Speech)** v2 is a model from Coqui that: - Supports **voice cloning** using just a short audio clip. - Can synthesize speech in **multiple languages**. - Is available on [Hugging Face](https://huggingface.co/coqui/XTTS-v2) and can be used **locally** or via **inference APIs**. --- ## 🧰 Requirements ### 1. Local Environment You'll need: - Python ≥ 3.8 - A GPU (NVIDIA recommended) or powerful CPU - `git`, `ffmpeg`, `torch`, and basic CLI tools ### 2. Python Packages Install: ```bash pip install -U coqui-xtts torch torchaudio ``` You may need to install other dependencies manually, like `ffmpeg`. --- ## 📁 Step 1: Prepare the Voice Sample - Record or use an existing **clean 3–10 second audio sample** of the voice you want to clone. - Recommended format: `.wav`, **16-bit PCM**, mono, **16kHz** sample rate. Example: ```bash ffmpeg -i yourfile.mp3 -ar 16000 -ac 1 -sample_fmt s16 cloned_voice.wav ``` --- ## 📦 Step 2: Load the Model Create a Python script or open a Python shell: ```python from TTS.api import TTS # Load the XTTS model tts = TTS(model_name="tts_models/multilingual/multi-dataset/xtts_v2", progress_bar=True) ``` > ⚠️ On first use, it will download the model from Hugging Face and cache it locally. --- ## 🎤 Step 3: Clone the Voice Use your `cloned_voice.wav` file and generate speech with any text: ```python tts.tts_to_file( text="Hello, this is your voice speaking from the future!", speaker_wav="cloned_voice.wav", language="en", file_path="output.wav" ) ``` You can adjust `text` and `language` (e.g., `"es"`, `"de"`, `"fr"`, etc.) --- ## 🧪 Optional: Use Voice Embeddings (Advanced) You can extract and reuse the voice embedding for efficiency: ```python # Get voice embedding embed = tts.get_speaker_embedding("cloned_voice.wav") # Reuse it: tts.tts_to_file( text="Another sentence with the same voice.", speaker_embedding=embed, language="en", file_path="second_output.wav" ) ``` --- ## 🧪 Optional: Run with Gradio UI If you prefer not to code, Coqui provides a Gradio demo: ```bash git clone https://github.com/coqui-ai/TTS cd TTS pip install -r requirements.txt python TTS/tts/models/xtts/gradio_app.py ``` This launches a local web UI for testing voice cloning and speech synthesis. --- ## 🚀 Deploying via Hugging Face Inference API You can use the Hugging Face-hosted model if you don’t want to run it locally (note: may have limited access or require a Pro account): ```python from huggingface_hub import InferenceClient client = InferenceClient("coqui/XTTS-v2") audio = client.text_to_speech( "This is the API response with the cloned voice.", voice="en_sample", model="coqui/XTTS-v2" ) ``` Check Hugging Face’s page for rate limits and sample voices. --- ## 📌 Tips for Better Results - Use **high-quality audio** (no background noise, clipping, or echo). - Trim silence at beginning/end. - Keep input text **natural and clear**. - Try different speaker samples if quality is low. --- ## 📁 File Output - You’ll get an `output.wav` file, ready for playback or integration into other applications. - Convert it to mp3, stream it, or feed it into a game/app, depending on your use case. --- ## ✅ Summary | Step | Description | |------|-------------| | 1 | Install Python and Coqui XTTS | | 2 | Prepare clean voice sample | | 3 | Load the XTTS model | | 4 | Use `tts.tts_to_file()` to synthesize voice | | 5 (Optional) | Use speaker embeddings or Gradio UI | --- If you’d like, I can generate a shell script or notebook version to speed up local usage. Just let me know.