Hoon_ Chung_jsut_asr_train_asr_conformer8_raw_char_sp_valid.acc.ave

Introduction

The model "Hoon_Chung_jsut_asr_train_asr_conformer8_raw_char_sp_valid.acc.ave" is an Automatic Speech Recognition (ASR) model from the ESPnet library. It is designed for Japanese language audio processing and is based on the jsut dataset. The model is part of the larger ESPnet toolkit, known for end-to-end speech processing capabilities.

Architecture

The model utilizes a Conformer architecture, which is an advanced neural network structure that combines convolutional neural networks with transformers. This architecture is particularly effective in capturing long-range dependencies in audio data while maintaining computational efficiency. The model was developed using the jsut/asr1 recipe in ESPnet.

Training

The model was trained by Hoon Chung and imported from Zenodo. Training was conducted using the ESPnet toolkit, which facilitates end-to-end ASR development. The jsut dataset, a collection of Japanese audio samples, was used to train the model, focusing on character-based speech recognition.

Guide: Running Locally

To run this model locally, follow these basic steps:

1. Setup Environment: Ensure you have Python and necessary libraries installed. You may need to install ESPnet by cloning its GitHub repository.
2. Download Model: Obtain the model from Hugging Face's model hub or Zenodo.
3. Prepare Data: Use the jsut dataset or similar Japanese audio data.
4. Run Inference: Utilize ESPnet's inference scripts to transcribe audio files.

For enhanced performance, consider using cloud GPUs from providers like AWS, Google Cloud, or Azure, which offer scalable resources for model inference.

License

The model is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0). This allows for sharing and adaptation with appropriate credit given to the original authors.