Parler TTS Mini v0.1
| Property | Value |
|---|---|
| Parameter Count | 647M |
| License | Apache 2.0 |
| Paper | View Paper |
| Training Data | 10.5K hours |
| Language | English |
What is parler_tts_mini_v0.1?
Parler TTS Mini v0.1 is a groundbreaking lightweight text-to-speech model that represents the first release from the Parler-TTS project. Built using transformer architecture, this model has been trained on 10.5K hours of audio data and offers remarkable control over speech generation through simple text prompts.
Implementation Details
The model utilizes a transformer-based architecture with 647M parameters, implementing F32 tensor types for precise audio generation. It's built on the HuggingFace transformers library and requires minimal setup for deployment. The model processes both text input and descriptive prompts to generate highly customizable speech output.
- Simple installation via pip
- Cuda-compatible for GPU acceleration
- Built-in tokenizer for text processing
- Supports real-time audio generation
Core Capabilities
- Natural speech generation with controllable features
- Gender selection through prompts
- Adjustable speaking rate and pitch
- Background noise control
- Environment acoustics (reverberation) adjustment
- Prosody control through punctuation
Frequently Asked Questions
Q: What makes this model unique?
The model's ability to control multiple speech aspects through natural language descriptions sets it apart, along with being fully open-source and having permissive licensing. Its lightweight nature (647M parameters) makes it accessible while maintaining high-quality output.
Q: What are the recommended use cases?
The model is ideal for applications requiring customizable text-to-speech, including audiobook creation, virtual assistants, content accessibility, and educational materials. It's particularly useful when specific voice characteristics or environmental effects are needed.
