---
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 6338735137.714
    num_examples: 16143
  download_size: 6016375356
  dataset_size: 6338735137.714
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
task_categories:
- automatic-speech-recognition
language:
- ja
tags:
- anime
- japanese
- 日本語
- nihongo
- speech
- audio-text
- asr
- whisper
pretty_name: Japanese-Anime-Speech
size_categories:
- 10K<n<100K
license: cc0-1.0
---
# Japanese Anime Speech Dataset

**japanese-anime-speech** is an audio-text dataset designed for the training of automatic speech recognition models. The dataset is comprised of thousands of audio clips and their corresponding transcriptions from different visual novels.

The goal of this dataset is to enhance the proficiency of automatic speech recognition systems, such as OpenAI's [Whisper](https://huggingface.co/openai/whisper-large-v2), in accurately transcribing dialogue from anime and other similar Japanese media. This genre is characterized by unique linguistic features and speech patterns that diverge from conventional Japanese speech.

# Changelog

* V1 - This version contains **16,143** audio-text pairs from the visual novel `IxSHE Tell`. Some cleaning of the transcriptions has been done to get rid of unwanted characters at the start and end of lines, but I intend to do much more for the second version.

* V2 - The version contains **23,422** audio-text pairs from three different visual novels. Cleaning has been done to remove most nsfw lines, especially noises that aren't words. The audio is now in mp3 format, rather than wav. This version contains **32.6** hours of audio.

* **V3** - The dataset now contains **38,325** audio-text pairs from five different visual novels. Very thorough cleaning has been done to remove almost all nsfw or low-quality audio files. Transcriptions have been formatted to contain much fewer dramatised duplicated characters (for example 「ああああーーー」), and transcriptions have been made much more consistent (for example, using the same type of quotation mark). This version contains **52.5 hours** of audio.

# Dataset information

* **38,325** audio-text pairs
* **52.5 hours** of audio (OpenAI suggests a minimum of [5 hours](https://huggingface.co/blog/fine-tune-whisper) for productive [Whisper](https://huggingface.co/openai/whisper-large-v2) fine-tuning).
* **4.9s** average audio length.
* **All** transcriptions have been scraped directly from the game files of visual novels.

<div class="course-tip course-tip-orange bg-gradient-to-br dark:bg-gradient-to-r before:border-orange-500 dark:before:border-orange-800 from-orange-50 dark:from-gray-900 to-white dark:to-gray-950 border border-orange-50 text-orange-700 dark:text-gray-400">
  <p><b>Content Warning:</b> Please be advised that the majority of the audio in this dataset is sourced from visual novels and may include content that is not suitable for all audiences, such as suggestive sounds or mature topics. Efforts have been undertaken to minimise this content as much as possible. </p>
</div>

# To do

* [X] Create a dataset of over 10k items
* [X] Create a dataset of over 20k items
* [X] Compress the audio with minimal quality loss
* [X] Create a dataset of over 30k items
* [ ] Create more workflows for scraping audio from visual novels that use an engine other than Artemis
* [ ] Add audio from more visual novels
* [ ] Convert names in transcriptions to katakana?

# Use & Credit

This dataset is openly available for commercial or non-commercial use. Anyone is welcome to use this resource as they deem appropriate. However, the creator assumes no responsibility for the consequences of its use. While not mandatory, crediting this dataset with a hyperlink in any derivative work would be greatly appreciated.

I hope that by sharing this dataset, we (the open-source community) improve automatic speech recognition for anime content.