README.md

---
license: cc-by-nc-4.0
language:
- ru
- de
- en
task_categories:
- automatic-speech-recognition
tags:
- cs-fleurs
- code-switching
- codeswitching
- pier
- speech-recognition
- asr
- embedded-english
- tagged-transcripts
pretty_name: CS-FLEURS Tagged
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: id
    dtype: string
  - name: audio
    dtype: audio
  - name: language_pair
    dtype: string
  - name: matrix_language
    dtype: string
  - name: embedded_language
    dtype: string
  - name: duration_ms
    dtype: int64
  - name: text_tagged
    dtype: string
  - name: text_plain
    dtype: string
  - name: embedded_words
    sequence: string
  - name: source_dataset
    dtype: string
  splits:
  - name: test
    num_bytes: 191698185.0
    num_examples: 635
  download_size: 185921200
  dataset_size: 191698185.0
---

# CS-FLEURS Tagged

CS-FLEURS Tagged provides tagged transcripts for test split of Russian-English and
German-English code-switching utterances. The annotations mark embedded English
words in the reference transcript so they can be evaluated directly with
Point-of-Interest Error Rate (PIER).

Tagged words use the following format:

```text
<tag WORD>
```

For example:

```text
<tag Romanticism> во многом включал в себя <tag cultural> детерминизм
```

In this example, `Romanticism` and `cultural` are the embedded English words of
interest.

## Dataset Contents

The dataset currently contains two CS-FLEURS-test language pairs:

| Language pair | Description |
|---|---|
| `rus-eng` | Russian matrix language with embedded English words |
| `deu-eng` | German matrix language with embedded English words |

Each example includes the utterance audio, a tagged transcript, a plain
transcript with tags removed, and the list of tagged embedded English words.

## Columns

- `audio`: utterance audio
- `id`: utterance id
- `language_pair`: language pair, for example `rus-eng` or `deu-eng`
- `matrix_language`: matrix language code
- `embedded_language`: embedded language code, currently `eng`
- `duration_ms`: utterance duration in milliseconds
- `text_tagged`: transcript with `<tag ...>` annotations
- `text_plain`: transcript with tags removed
- `embedded_words`: list of tagged embedded English words
- `source_dataset`: original source dataset id

## Usage

Load the dataset with `datasets`:

```python
from datasets import load_dataset

ds = load_dataset("YapayNet/cs-fleurs-tagged", split="test")

example = ds[0]
print(example["id"])
print(example["text_tagged"])
print(example["embedded_words"])
print(example["audio"])
```

The `text_tagged` field can be used when the evaluation needs to preserve the
explicit points of interest. The `text_plain` field is useful for standard ASR
evaluation or display. The `embedded_words` field provides the tagged words as a
list.

## PIER Evaluation

This dataset is designed for code-switching ASR evaluation with PIER, a metric
that focuses evaluation on selected words of interest instead of only reporting
aggregate WER.

Use the PIER evaluation code from:

[enesyugan/PIER-CodeSwitching-Evaluation](https://github.com/enesyugan/PIER-CodeSwitching-Evaluation)

The annotation and tagging setup is described in:

[enesyugan/robust-code-switching-asr](https://github.com/enesyugan/robust-code-switching-asr)

## Source Dataset

This dataset is derived from CS-FLEURS test split:

[byan/cs-fleurs](https://huggingface.co/datasets/byan/cs-fleurs)

Audio and base transcripts come from CS-FLEURS. The `<tag ...>` annotations were
added for PIER-style code-switching evaluation.

## License

This dataset follows the license of the source dataset: CC BY-NC 4.0.

## Citation

If you use this dataset, please cite CS-FLEURS, how it was tagged ugan2026adding and if you evaluate using PIER ugan2025pier.

```bibtex
@article{ugan2026adding,
  title={Adding Robust Code-Switching Capabilities to High Performance Multilingual ASR},
  author={Ugan, Enes Yavuz and Waibel, Alexander},
  journal={arXiv preprint arXiv:2606.21990},
  year={2026}
}
```

```bibtex
@article{yan2025cs,
  title={CS-FLEURS: A Massively Multilingual and Code-Switched Speech Dataset},
  author={Yan, Brian and Hamed, Injy and Shimizu, Shuichiro and Lodagala, Vasista and Chen, William and Iakovenko, Olga and Talafha, Bashar and Hussein, Amir and Polok, Alexander and Chang, Kalvin and others},
  journal={arXiv preprint arXiv:2509.14161},
  year={2025}
}
```

```bibtex
@misc{ugan2025pier,
  title={PIER: A Novel Metric for Evaluating What Matters in Code-Switching},
  author={Ugan, Enes Yavuz and Pham, Ngoc-Quan and Bärmann, Leonard and Waibel, Alex},
  year={2025},
  eprint={2501.09512},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}
```