spark-tts-lib 0.2.1

A Python package for Spark-TTS.

Spark-TTS-Lib

A Python package for Spark-TTS

📦 Install

pip install spark-tts-lib

🌟 Sample Example

from spark_tts_lib import SparkTTS

model = SparkTTS()
wav_data = model.inference(text="Hello, world!")

🚀 Usage

Download the pretrained model:

from spark_tts_lib import download_pretrained_model

download_pretrained_model()

The model will be downloaded to the pretrained_models/Spark-TTS-0.5B directory in the current directory. You can also specify a directory to save it.

download_pretrained_model(local_dir="/path/to/save/model")

You can also download the model from the Hugging Face page.

Import SparkTTS:

from spark_tts_lib import SparkTTS

Initialize the model:

model = SparkTTS()

If you want to specify the model directory, you can do it like this:

model_dir = "pretrained_models/Spark-TTS-0.5B"
model = SparkTTS(model_dir)

Perform voice creation inference:

text = "This is the text you want to synthesize into speech."
gender = "female" # "male"
pitch = "high" # "very_low" | "low" | "moderate" | "high" | "very_high"
speed = "high" # "very_low" | "low" | "moderate" | "high" | "very_high"

wav_data = model.inference(text=text, gender=gender, pitch=pitch, speed=speed)

Perform voice cloning inference:

text = "This is the text you want to synthesize into speech."
prompt_speech_path = "prompt_audio.wav"
prompt_text = "This is the text corresponding to your reference audio."

wav_data = model.inference(
    text=text,
    prompt_speech_path=prompt_speech_path,
    prompt_text=prompt_text,
)

Inference with more parameters:

model.inference(
    ...
    temperature=0.8,
    top_k=50,
    top_p=0.95,
)

📚 More information

Please refer to the Spark-TTS for more details.

⚠️ Usage Disclaimer

This project provides a zero-shot voice cloning TTS model intended for academic research, educational purposes, and legitimate applications, such as personalized speech synthesis, assistive technologies, and linguistic research.

Please note:

• Do not use this model for unauthorized voice cloning, impersonation, fraud, scams, deepfakes, or any illegal activities.

• Ensure compliance with local laws and regulations when using this model and uphold ethical standards.

• The developers assume no liability for any misuse of this model.

We advocate for the responsible development and use of AI and encourage the community to uphold safety and ethical principles in AI research and applications. If you have any concerns regarding ethics or misuse, please contact us.