icefall asr gigaspeech2 vi zipformer

Introduction

The ICEFALL-ASR-GIGASPEECH2-VI-ZIPFORMER is a speech recognition model that leverages the ONNX framework. It is designed to work with the Gigaspeech dataset, offering efficient processing capabilities for Vietnamese language speech recognition tasks.

Architecture

The model employs the Zipformer architecture, which is known for optimizing computational resources while maintaining high accuracy in automated speech recognition (ASR) tasks. The architecture is tailored to handle large-scale speech data efficiently.

Training

Details on the specific training methodologies, datasets, and hyperparameters used for training this model are not provided in the README. However, it is likely trained on the Gigaspeech dataset with a focus on Vietnamese language processing, utilizing the capabilities of the Zipformer architecture for optimized performance.

Guide: Running Locally

To run the ICEFALL-ASR-GIGASPEECH2-VI-ZIPFORMER model locally, follow these steps:

1. Clone the Repository: Obtain the model's repository from Hugging Face using Git.
2. Install ONNX: Ensure that the ONNX runtime is installed in your environment for model inference.
3. Environment Setup: Create a Python environment with the necessary dependencies.
4. Run Inference: Use the provided scripts or your own code to perform speech recognition tasks with the model.

For enhanced performance, it is recommended to use a cloud GPU service such as AWS, Azure, or Google Cloud, which can provide the necessary computational resources for efficient model execution.

License

The ICEFALL-ASR-GIGASPEECH2-VI-ZIPFORMER model is licensed under the Apache 2.0 License. This allows for both personal and commercial use, with conditions regarding attribution and liability.