Datasets:
Update README.md
Browse files
README.md
CHANGED
@@ -69,18 +69,6 @@ A list of all audio files and transcriptions are [**here**](https://huggingface.
|
|
69 |
* **5.4s** average audio length
|
70 |
* Transcriptions have been scraped directly from the game files of **visual novels**
|
71 |
|
72 |
-
# To do
|
73 |
-
|
74 |
-
- [X] Create a dataset of over 10k items
|
75 |
-
- [X] Create a dataset of over 20k items
|
76 |
-
- [X] Compress the audio with minimal quality loss
|
77 |
-
- [X] Create a dataset of over 30k items
|
78 |
-
- [X] Create a dataset of over 40k items
|
79 |
-
- [X] Create a dataset of over 50k items
|
80 |
-
- [ ] Create more workflows for scraping audio from visual novels that use an engine other than Artemis
|
81 |
-
- [ ] Convert names in transcriptions to katakana?
|
82 |
-
- [ ] Scrape audio and transcriptions from YouTube
|
83 |
-
|
84 |
# Bias and Limitations
|
85 |
This dataset, while valuable for training anime-style Japanese speech recognition, has some inherent biases and limitations. The audio is primarily sourced from visual novels, leading to a gender bias towards female voices and a domain-specific vocabulary revolving around topics such as love, relationships, and fantasy. Additionally, the professionally produced nature of the audio results in clear and slow speech, which may not fully reflect real-world speaking patterns.
|
86 |
|
|
|
69 |
* **5.4s** average audio length
|
70 |
* Transcriptions have been scraped directly from the game files of **visual novels**
|
71 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
72 |
# Bias and Limitations
|
73 |
This dataset, while valuable for training anime-style Japanese speech recognition, has some inherent biases and limitations. The audio is primarily sourced from visual novels, leading to a gender bias towards female voices and a domain-specific vocabulary revolving around topics such as love, relationships, and fantasy. Additionally, the professionally produced nature of the audio results in clear and slow speech, which may not fully reflect real-world speaking patterns.
|
74 |
|