Whisper Small Ko Low Qual Voice

🚀 Model Card for whisper-small-ko-finetuned

This is a fine - tuned model based on SungBeom/whisper - small - ko, specialized for Korean automatic speech recognition, delivering excellent performance on validation sets.

🚀 Quick Start

from transformers import WhisperProcessor, WhisperForConditionalGeneration
import torch

model = WhisperForConditionalGeneration.from_pretrained("your-username/whisper-small-ko-finetuned")
processor = WhisperProcessor.from_pretrained("your-username/whisper-small-ko-finetuned")

# Input: 16kHz waveform (float32 numpy or tensor)
inputs = processor(audio_waveform, sampling_rate=16000, return_tensors="pt")

with torch.no_grad():
    predicted_ids = model.generate(inputs.input_features)

transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)
print(transcription[0])

✨ Features

• Performs automatic speech recognition (ASR) for Korean audio data.
• Can be used for offline or batch transcription of Korean speech data.
• Suitable for integration into Korean - language voice assistant systems.
• Allows for further fine - tuning on domain - specific datasets.

📚 Documentation

Model Details

Model Description

This model is based on the Whisper - small architecture and fine - tuned on 62,327 Korean audio - transcript pairs using Hugging Face Transformers and PyTorch. It is designed for general - domain Korean speech recognition (conversational, broadcast, news, etc.).

Model Sources

• Repository: [https://huggingface.co/kimthegarden/whisper-small-ko-low-qual-voice]
• Notebook: Fine - tuned using a custom whisper_finetuning.ipynb
• Demo [optional]: [Gradio or Streamlit demo link if available]

Uses

Direct Use

• Korean automatic speech recognition (ASR)
• Offline or batch transcription of Korean speech data
• Integration into Korean - language voice assistant systems

Downstream Use

• Further fine - tuning on domain - specific datasets (e.g. legal, medical, education)
• Research into Korean ASR model robustness or multilingual Whisper models

Out - of - Scope Use

• Transcription of non - Korean speech (this model is Korean - only)
• Real - time streaming ASR (not latency - optimized)
• Zero - shot or few - shot adaptation to other languages

Bias, Risks, and Limitations

• The model may show reduced accuracy on:
  • Regional dialects or accents not represented in the training data
  • Very noisy environments
  • Children’s speech or non - native pronunciation
• The model has not been tested for fairness across different speakers (gender, age, etc.)

⚠️ Important Note

The model may have reduced accuracy in certain scenarios such as on regional dialects, in noisy environments, or for children's speech. Also, fairness across different speakers has not been tested.

💡 Usage Tip

We recommend testing the model on your specific data domain before deployment. Additional fine - tuning or data filtering may be required for sensitive use cases (e.g. education, healthcare).

📄 License

This model is released under the MIT license.