README.md

---
dataset_info:
- config_name: default
  features:
  - name: audio_filename
    dtype: string
  - name: folder
    dtype: string
  - name: text
    dtype: string
  - name: start
    dtype: float64
  - name: end
    dtype: float64
  - name: speaker
    dtype: string
  - name: language
    dtype: string
  - name: dnsmos
    dtype: float64
  splits:
  - name: train
    num_bytes: 367597240
    num_examples: 605169
  download_size: 103343988
  dataset_size: 367597240
- config_name: speaker_permutation
  features:
  - name: reference_audio
    dtype: string
  - name: reference_text
    dtype: string
  - name: target_audio
    dtype: string
  - name: target_text
    dtype: string
  splits:
  - name: train
    num_bytes: 17529497076
    num_examples: 18420256
  download_size: 203132504
  dataset_size: 17529497076
- config_name: speaker_permutation_sample
  features:
  - name: reference_audio
    dtype: string
  - name: reference_text
    dtype: string
  - name: target_audio
    dtype: string
  - name: target_text
    dtype: string
  splits:
  - name: train
    num_bytes: 1277986515
    num_examples: 1345148
  download_size: 203603198
  dataset_size: 1277986515
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
- config_name: speaker_permutation
  data_files:
  - split: train
    path: speaker_permutation/train-*
- config_name: speaker_permutation_sample
  data_files:
  - split: train
    path: speaker_permutation_sample/train-*
---

# Malaysian-Chinese-Emilia

Use https://github.com/mesolitica/Emilia to pseudo-label Malaysian Chinese audio.

- Total rows: 605169
- Total hours: 1857.611445057867 hours

## Permutation for Voice Conversion

Also we already calculated speaker permutation to prepare for voice conversion.