---
language:
- zh
language_bcp47:
- zh-TW
- cmn-TW
license: cc0-1.0
task_categories:
- automatic-speech-recognition
pretty_name: Common Voice Scripted Speech 25.0 - Chinese (Taiwan)
tags:
- common-voice
- scripted-speech
- asr
- audio
- speech
- zh-TW
- cmn-TW
size_categories:
- 100K<n<1M
dataset_info:
  features:
  - name: audio
    dtype:
      audio:
        sampling_rate: 48000
  - name: client_id
    dtype: string
  - name: path
    dtype: string
  - name: sentence_id
    dtype: string
  - name: sentence
    dtype: string
  - name: sentence_domain
    dtype: string
  - name: up_votes
    dtype: int32
  - name: down_votes
    dtype: int32
  - name: age
    dtype: string
  - name: gender
    dtype: string
  - name: accents
    dtype: string
  - name: variant
    dtype: string
  - name: locale
    dtype: string
  - name: segment
    dtype: string
  - name: duration_ms
    dtype: int32
  splits:
  - name: train
    num_bytes: 159568965
    num_examples: 7394
  - name: validation
    num_bytes: 129109947
    num_examples: 5119
  - name: test
    num_bytes: 147751267
    num_examples: 5119
  - name: validated
    num_bytes: 2453301339
    num_examples: 85324
  - name: invalidated
    num_bytes: 116251455
    num_examples: 4920
  - name: other
    num_bytes: 1066740808
    num_examples: 50386
  download_size: 3670777901
  dataset_size: 4072723781
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
  - split: validated
    path: data/validated-*
  - split: invalidated
    path: data/invalidated-*
  - split: other
    path: data/other-*
---

# Common Voice Scripted Speech 25.0 - Chinese (Taiwan)

This repository mirrors the Chinese (Taiwan) (`zh-TW`) portion of Mozilla Common Voice Scripted Speech 25.0 in Hugging Face `datasets` format. The audio has been embedded into Parquet and exposed as a Hugging Face `Audio` feature at 48 kHz.

Official source page: [Mozilla Data Collective - Common Voice Scripted Speech 25.0 - Chinese (Taiwan)](https://mozilladatacollective.com/datasets/cmn2g7eaj01fio10769r1m96n)

## Dataset Details

| Field | Value |
| --- | --- |
| Dataset ID | `cmn2g7eaj01fio10769r1m96n` |
| Common Voice release | `cv-corpus-25.0-2026-03-09` |
| Language | Chinese (Taiwan), 華語（台灣）, `zh-TW` |
| Spoken variety | Taiwan Mandarin / 中華民國國語, `cmn-TW` |
| Task | Automatic Speech Recognition (ASR) |
| Original format | MP3 |
| Original archive | `common-voice-scripted-speech-25-0-chines-e84858c5.tar.gz` |
| Original archive size | 2.95 GB |
| Release date on Mozilla Data Collective | 2026-03-23 |
| License | Creative Commons Zero v1.0 Universal (CC0-1.0) |

The original Mozilla metadata describes this as a collection of read speech recordings in Chinese (Taiwan). It contains 140,630 clips from 2,317 self-selected volunteer speakers, totaling 131.33 hours of speech. Of those clips, 85,324 are validated, corresponding to 79.68 validated hours. The sentence pool contains 21,763 sentences.

## Important Usage Notes

The source dataset is released under CC0-1.0. The Mozilla Data Collective page also lists additional restrictions and constraints:

- Do not attempt to determine the identity of speakers in Common Voice datasets.
- The source page states that re-hosting or re-sharing the dataset is forbidden.
- Use of this mirror should follow the Mozilla Data Collective dataset page and its current terms.

Speaker demographic fields are self-reported and optional. Blank values mean the speaker did not provide that field.

## Loading

```python
from datasets import load_dataset

ds = load_dataset("OpenFormosa/common_voice_25_zh-TW", split="train")
print(ds.features["audio"])
print(ds[0]["sentence"])
```

For quick inspection without downloading full splits:

```python
from datasets import load_dataset, Audio

stream = load_dataset("OpenFormosa/common_voice_25_zh-TW", split="train", streaming=True)
stream = stream.cast_column("audio", Audio(sampling_rate=48000, decode=False))
row = next(iter(stream))
print(row["audio"])
print(row["sentence"])
```

## Splits

The train, validation, and test splits are the official Common Voice training subsets. The `validated`, `invalidated`, and `other` splits preserve the broader Common Voice clip buckets. The training subsets are drawn from the validated bucket, so they should not be treated as disjoint from `validated`.

| Split | Rows | Notes |
| --- | ---: | --- |
| `train` | 7,394 | Official training split |
| `validation` | 5,119 | Original `dev.tsv` |
| `test` | 5,119 | Official test split |
| `validated` | 85,324 | Validated clips |
| `invalidated` | 4,920 | Clips that did not pass validation |
| `other` | 50,386 | Clips pending validation or otherwise outside validated/invalidated |

Mozilla's metadata reports 17,632 train/dev/test clips, covering 20.7% of validated clips. The average clip duration is 3.362 seconds.

## Features

| Column | Type | Description |
| --- | --- | --- |
| `audio` | `Audio(sampling_rate=48000)` | Embedded MP3 audio exposed through the Hugging Face `Audio` feature |
| `client_id` | string | Hashed speaker identifier from Common Voice |
| `path` | string | Original relative MP3 filename |
| `sentence_id` | string | Common Voice sentence identifier |
| `sentence` | string | Expected transcription text |
| `sentence_domain` | string | Sentence domain label; may be blank or contain multiple comma-separated domains |
| `up_votes` | int32 | Number of validators who accepted the clip |
| `down_votes` | int32 | Number of validators who rejected the clip |
| `age` | string | Self-reported speaker age bucket |
| `gender` | string | Self-reported speaker gender |
| `accents` | string | Self-reported accent or place-of-origin label |
| `variant` | string | Language variant, if provided |
| `locale` | string | Locale code, normally `zh-TW` |
| `segment` | string | Custom dataset segment, if provided |
| `duration_ms` | int32 | Clip duration from `clip_durations.tsv` |

The original source files are also included under `source/`:

- `source/README.zh-TW.md`
- `source/train.tsv`
- `source/dev.tsv`
- `source/test.tsv`
- `source/validated.tsv`
- `source/invalidated.tsv`
- `source/other.tsv`
- `source/reported.tsv`
- `source/validated_sentences.tsv`
- `source/unvalidated_sentences.tsv`
- `source/clip_durations.tsv`

## Demographics

### Gender

| Code | Label | Clips | Speakers |
| --- | --- | ---: | ---: |
| `male_masculine` | Male, masculine | 68,527 (48.7%) | 598 (25.8%) |
| `female_feminine` | Female, feminine | 31,056 (22.1%) | 258 (11.1%) |
| `transgender` | Transgender | 100 (0.1%) | 1 (0.0%) |
| `non-binary` | Non-binary | 0 | 0 |
| `do_not_wish_to_say` | Prefer not to say | 25 (0.0%) | 2 (0.1%) |
| Unspecified | Not declared | 40,922 (29.1%) | 1,575 (68.0%) |

Gender declared: 99,708 of 140,630 clips (70.9%), 742 of 2,317 speakers (32.0%).

### Age

| Code | Label | Clips | Speakers |
| --- | --- | ---: | ---: |
| `teens` | Teens | 8,440 (6.0%) | 82 (3.5%) |
| `twenties` | Twenties | 41,664 (29.6%) | 451 (19.5%) |
| `thirties` | Thirties | 27,021 (19.2%) | 231 (10.0%) |
| `fourties` | Fourties | 12,771 (9.1%) | 105 (4.5%) |
| `fifties` | Fifties | 12,587 (9.0%) | 27 (1.2%) |
| `sixties` | Sixties | 431 (0.3%) | 3 (0.1%) |
| `seventies` | Seventies | 30 (0.0%) | 4 (0.2%) |
| `eighties` | Eighties | 0 | 0 |
| `nineties` | Nineties | 0 | 0 |
| Unspecified | Not declared | 37,686 (26.8%) | 1,540 (66.5%) |

Age declared: 102,944 of 140,630 clips (73.2%), 777 of 2,317 speakers (33.5%).

## Accent Distribution

The source page reports self-declared accent or place-of-origin coverage as follows.

| Code | Label | Clips | Speakers |
| --- | --- | ---: | ---: |
| `taipei_city` | 出生地：臺北市 | 19,646 (14.0%) | 107 (4.6%) |
| `new_taipei_city` | 出生地：新北市 | 8,850 (6.3%) | 62 (2.7%) |
| `taichung_city` | 出生地：臺中市 | 4,411 (3.1%) | 47 (2.0%) |
| `kaohsiung_city` | 出生地：高雄市 | 3,266 (2.3%) | 42 (1.8%) |
| `taoyuan_city` | 出生地：桃園市 | 3,015 (2.1%) | 23 (1.0%) |
| `hsinchu_city` | 出生地：新竹市 | 2,866 (2.0%) | 11 (0.5%) |
| `yunlin_county` | 出生地：雲林縣 | 2,560 (1.8%) | 8 (0.3%) |
| `nantou_county` | 出生地：南投縣 | 2,101 (1.5%) | 7 (0.3%) |
| `changhua_county` | 出生地：彰化縣 | 2,009 (1.4%) | 22 (0.9%) |
| `tainan_city` | 出生地：臺南市 | 1,708 (1.2%) | 21 (0.9%) |
| `chiayi_city` | 出生地：嘉義市 | 1,195 (0.8%) | 5 (0.2%) |
| `pingtung_county` | 出生地：屏東縣 | 913 (0.6%) | 6 (0.3%) |
| `hualien_county` | 出生地：花蓮縣 | 878 (0.6%) | 5 (0.2%) |
| `yilan_county` | 出生地：宜蘭縣 | 765 (0.5%) | 8 (0.3%) |
| `hong_kong` | 香港 | 690 (0.5%) | 26 (1.1%) |
| `chiayi_county` | 出生地：嘉義縣 | 379 (0.3%) | 7 (0.3%) |
| `hsinchu_county` | 出生地：新竹縣 | 343 (0.2%) | 8 (0.3%) |
| `keelung_city` | 出生地：基隆市 | 141 (0.1%) | 10 (0.4%) |
| `kinmen_county` | 出生地：金門縣 | 55 (0.0%) | 1 (0.0%) |
| `penghu_county` | 出生地：澎湖縣 | 20 (0.0%) | 2 (0.1%) |
| `miaoli_county` | 出生地：苗栗縣 | 15 (0.0%) | 2 (0.1%) |
| `taitung_county` | 出生地：臺東縣 | 10 (0.0%) | 2 (0.1%) |
| Other | Other accent strings | 5,017 (3.6%) | 21 (0.9%) |

## Sentence Corpus

Most Traditional Chinese text was organized through the [MozTW CC0 sentence corpus](https://github.com/moztw/cc0-sentences). Mozilla's metadata reports:

- Validated sentences: 20,786
- Unvalidated sentences: 977
- Pending sentences: 137
- Rejected sentences: 840
- Reported sentences: 179
- Total sentence pool: 21,763

Sentence source distribution:

| Source | Sentences |
| --- | ---: |
| `sentence-collector` | 15,566 (74.9%) |
| `setences` | 2,897 (13.9%) |
| MozTW CC0 corpus commit `01033097...` | 666 (3.2%) |
| MozTW CC0 corpus commit `e340b6d...` | 451 (2.2%) |
| `taipei_city_gov` | 355 (1.7%) |
| `chatlogs` | 309 (1.5%) |
| Other | 533 (2.6%) |

## Sentence Domains

The source page reports the following domain coverage among clips. In this Hugging Face version, `sentence_domain` is preserved as the raw Common Voice field and may be empty or contain multiple comma-separated values.

| Code | Domain | Clips | Speakers |
| --- | --- | ---: | ---: |
| `general` | General | 1,502 (1.1%) | 84 (3.6%) |
| `agriculture_food` | Agriculture and Food | 12 (0.0%) | 7 (0.3%) |
| `automotive_transport` | Automotive and Transport | 278 (0.2%) | 45 (1.9%) |
| `finance` | Finance | 3 (0.0%) | 3 (0.1%) |
| `service_retail` | Service and Retail | 151 (0.1%) | 36 (1.6%) |
| `healthcare` | Healthcare | 25 (0.0%) | 18 (0.8%) |
| `history_law_government` | History, Law and Government | 170 (0.1%) | 39 (1.7%) |
| `media_entertainment` | Media and Entertainment | 170 (0.1%) | 44 (1.9%) |
| `nature_environment` | Nature and Environment | 14 (0.0%) | 12 (0.5%) |
| `news_current_affairs` | News and Current Affairs | 44 (0.0%) | 19 (0.8%) |
| `technology_robotics` | Technology and Robotics | 777 (0.6%) | 49 (2.1%) |
| `language_fundamentals` | Language Fundamentals | 8 (0.0%) | 7 (0.3%) |

## Intended Uses

Mozilla lists the intended use as training and evaluating automatic speech recognition models. The dataset may also be useful for computer-aided language learning and language or heritage revitalization applications.

## Provenance and Acknowledgements

The text corpus was created by Mozilla Taiwan community contributors, the g0v community, and other open-source volunteers. Speakers are primarily individual volunteers from Taiwan.

Mozilla's metadata names Irvin Chen as the MozTW community contact for dataset table preparation.

## License

The dataset is released under [Creative Commons Zero v1.0 Universal](https://spdx.org/licenses/CC0-1.0.html). Users should also review the [Mozilla Data Collective dataset page](https://mozilladatacollective.com/datasets/cmn2g7eaj01fio10769r1m96n) for current restrictions and terms before use.