MMS-LID-126
| Property | Value |
|---|---|
| Parameter Count | 1 billion |
| Model Type | Multilingual Speech Recognition |
| Architecture | Wav2Vec2 |
| License | CC-BY-NC 4.0 |
| Audio Sample Rate | 16kHz |
What is mms-lid-126?
MMS-LID-126 is a sophisticated language identification model developed by Facebook as part of their Massively Multilingual Speech project. This model is specifically designed to identify the language being spoken in audio inputs across 126 different languages, making it one of the most comprehensive language identification systems available.
Implementation Details
Built on the Wav2Vec2 architecture, the model processes raw audio input at 16kHz sampling rate and outputs probability distributions across 126 language classes. It has been fine-tuned from the facebook/mms-1b base model and comprises 1 billion parameters, enabling highly accurate language identification across a diverse range of linguistic inputs.
- Processes raw audio input at 16kHz sampling rate
- Uses transformers library for easy integration
- Outputs probability distribution over 126 languages
- Fine-tuned from facebook/mms-1b base model
Core Capabilities
- Accurate identification of 126 distinct languages
- Support for diverse linguistic families and regions
- Real-time audio processing capabilities
- Integration with popular ML frameworks through transformers library
Frequently Asked Questions
Q: What makes this model unique?
The model's ability to identify 126 different languages with high accuracy, combined with its massive scale of 1 billion parameters and foundation in the proven Wav2Vec2 architecture, makes it uniquely powerful for multilingual speech processing tasks.
Q: What are the recommended use cases?
The model is ideal for applications requiring automatic language identification from speech, such as multilingual call centers, content categorization systems, speech analytics platforms, and language-specific routing systems in audio processing pipelines.
