File size: 2,402 Bytes
c5d3877
c958513
 
c5d3877
c958513
 
e316510
 
c958513
e316510
 
 
 
 
c958513
 
 
 
 
 
 
 
 
 
 
 
253131f
fd30639
253131f
 
c958513
 
 
 
 
c5d3877
e316510
 
 
 
 
 
 
 
 
 
53b6049
e316510
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
---
language:
- en
license: mit
size_categories:
- n<1K
task_categories:
- text-to-speech
pretty_name: AniSpeech
tags:
- anime
- speech
- text-to-speech
- voice
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: caption
    dtype: string
  - name: phonetic captions
    dtype: string
  - name: voice
    dtype: string
  splits:
  - name: ENGLISH
    num_bytes: 18875728249.368
    num_examples: 23656
  download_size: 20449215803
  dataset_size: 18875728249.368
configs:
- config_name: default
  data_files:
  - split: ENGLISH
    path: data/ENGLISH-*
---

# AniSpeech Dataset

Welcome to the AniSpeech dataset, a continually expanding collection of captioned anime voices brought to you by ShoukanLabs.
- As we label more and more audio, they'll automagically be uploaded here for use, seperated by language

---

## Key Features

- **LJSpeech Format Compatibility:** The captions in this dataset can be converted to (recent changes have sacrificed native LJSpeech support for better captions) comply with the LJSpeech format, and we plan to offer conversion scripts to said format eventually.

- **Diverse Anime Voices:** Train your TTS models on high-quality vocal performances with variations in intonation, timbre, and pitch. The dataset offers a rich assortment of anime voices for creating generalised models.

- **Ideal for Generalized Models:** AniSpeech is a perfect choice for fine-tuning generalized models. With a diverse range of voices, it provides a solid foundation for training models that can handle a wide variety of speaking styles.

## Limitations

- **Single-Voice Fine-Tuning:** While AniSpeech excels in training foundation models (due to it's diversity), it's not recommended for fine-tuning on a single voice. Its strength lies in contributing to the development of versatile TTS models.

- **Dataset Curation:** Due to its size, manually curating the entire dataset can be impractical. If you encounter low-quality files or incorrect captions, we encourage you to contribute by creating a pull request to help maintain and improve the dataset.

## License

This dataset is released under the [MIT License](https://huggingface.co/datasets/ShoukanLabs/AniSpeech/raw/main/license).

Your contributions to the AniSpeech dataset are invaluable, and we appreciate your efforts in advancing the field of Text-to-Speech technology.

Happy coding and synthesizing!