Parler-TTS Mini v1
| Property | Value |
|---|---|
| Parameter Count | 878M parameters |
| License | Apache 2.0 |
| Paper | Research Paper |
| Training Data | 45K hours of audio data |
What is parler-tts-mini-v1?
Parler-TTS Mini v1 is a lightweight text-to-speech (TTS) model designed to generate high-quality, natural-sounding speech with controllable features. The model represents a significant advancement in accessible TTS technology, trained on an extensive dataset of 45,000 hours of audio data.
Implementation Details
The model is implemented using the Transformers architecture and operates on F32 tensor types. It's designed to be easily deployable through the HuggingFace ecosystem and can be controlled through simple text prompts.
- Simple installation through pip
- Supports both CPU and GPU inference
- Includes 34 pre-defined speaker profiles
- Uses natural language descriptions for voice control
Core Capabilities
- Voice characteristic control (gender, speaking rate, pitch)
- Background noise level adjustment
- Reverberation control
- Support for punctuation-based prosody control
- High-quality audio generation with variable characteristics
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its ability to control voice characteristics through natural language descriptions and its open-source nature, allowing full access to training code and weights under a permissive license.
Q: What are the recommended use cases?
The model is ideal for applications requiring customizable text-to-speech output, including content creation, accessibility tools, and educational applications. It's particularly useful when specific voice characteristics or quality levels are needed.
