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faster-whisper-Visual-novel-transcriptor

Automatic Speech Recognition
Transformers
Japanese
English
faster-whisper
ct2
ctranslate2
Model card Files Community
faster-whisper-Visual-novel-transcriptor
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---
library_name: transformers
datasets:
- reazon-research/reazonspeech
- joujiboi/japanese-anime-speech
language:
- ja
- en
metrics:
- cer
pipeline_tag: automatic-speech-recognition
tags:
- faster-whisper
- ct2
- ctranslate2
---

This is a faster-whisper/ct2 conversion of the original model:

[spow12/Visual-novel-transcriptor](https://huggingface.co/spow12/Visual-novel-transcriptor)

# Model Card for Model ID

Fine tunned ASR model from [distil-whisper/distil-large-v2](https://huggingface.co/distil-whisper/distil-large-v2).

This model aimed to transcribe japanese audio especially visual novel.

# WaifuModel Collections 

- [TTS](https://huggingface.co/spow12/visual_novel_tts)
- [Chat](https://huggingface.co/spow12/ChatWaifu_v1.2.1)
- [ASR](https://huggingface.co/spow12/Visual-novel-transcriptor)

# Unified Demo

[WaifuAssitant](https://github.com/yw0nam/WaifuAssistant)

## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** spow12(yw_nam)
- **Shared by :** spow12(yw_nam)
- **Model type:** Seq2Seq
- **Language(s) (NLP):** japanese
- **Finetuned from model :** [distil-whisper/distil-large-v2](https://huggingface.co/distil-whisper/distil-large-v2).


## Uses

```python
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
import librosa

processor = AutoProcessor.from_pretrained('spow12/Visual-novel-transcriptor', language="ja", task="transcribe")
model = AutoModelForSpeechSeq2Seq.from_pretrained('spow12/Visual-novel-transcriptor').cuda()
model.config.forced_decoder_ids = processor.get_decoder_prompt_ids(language="ja", task="transcribe")

data, _ = librosa.load(wav_path, sr=16000)
input_features = processor(data, sampling_rate=16000, return_tensors="pt").input_features.cuda()
predicted_ids = model.generate(input_features)
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)
print(transcription[0])
```

## Bias, Risks, and Limitations

This model trained by japanese dataset included visual novel which contain nsfw content.


## Use & Credit

This model is currently available for non-commercial use only. Also, since I'm not detailed in licensing, I hope you use it responsibly. 

By sharing this model, I hope to contribute to the research efforts of our community (the open-source community and anime persons).


## Citation

```bibtex
@misc {Visual-novel-transcriptor,
    author       = { YoungWoo Nam },
    title        = { Visual-novel-transcriptor },
    year         = 2024,
    url          = { https://huggingface.co/spow12/Visual-novel-transcriptor },
    publisher    = { Hugging Face }
}
```