README.md

---
license: cc-by-4.0
pretty_name: Klang Dialects
language:
- sv
task_categories:
- automatic-speech-recognition
size_categories:
- 1K<n<10K
tags:
- audio
- speech
- evaluation
- dialects
configs:
- config_name: sv-clean
  default: true
  data_files:
  - split: test
    path: data/sv/clean/test-*.parquet
- config_name: sv-raw
  data_files:
  - split: test
    path:
    - data/sv/clean/test-*.parquet
    - data/sv/raw-only/test-*.parquet
---

# Klang Dialects

Klang Dialects is an open benchmark for Swedish speech recognition, created by the Klang Research Team from recordings contributed through [Knäck Klang](https://knack.klang.ai).

The Swedish benchmark contains **1,804 recordings**, **656 speaker IDs**, and **5.15 hours of speech** in its main configuration, `sv-clean`. The benchmark supports research on regional variation in Swedish speech recognition. We plan to expand the dataset with more sentences, speakers, and languages.

## Configurations

| Configuration | Recordings | Speaker IDs | Hours |
|---|---:|---:|---:|
| `sv-clean` (default) | 1,804 | 656 | 5.15 |
| `sv-raw` | 1,883 | 658 | 5.43 |

**`sv-clean`** provides high-quality reference transcripts for standard word error rate (WER) comparisons.

**`sv-raw`** includes all of `sv-clean` plus 79 recordings with more than one reasonable reference transcription. These recordings remain useful for benchmarking, although even a perfect recognizer may score above 0% WER on them.

Both configurations use a single `test` split and the same seven fields.

## Loading

```python
from datasets import load_dataset

clean = load_dataset(
    "KlangAI/klang-dialects", "sv-clean", split="test", revision="v1.0"
)
raw = load_dataset(
    "KlangAI/klang-dialects", "sv-raw", split="test", revision="v1.0"
)
```

## Fields

| Field | Type | Description |
|---|---|---|
| `id` | string | Unique recording ID. |
| `audio` | Audio | Mono speech recording in 16-bit FLAC at 16 kHz. |
| `text` | string | Reference transcript, including capitalization and punctuation. |
| `speaker` | string | Anonymous speaker ID. A person who contributed more than once may have multiple IDs. |
| `region` | string or null | Contributor-supplied three-digit Swedish postcode prefix, where available. |
| `duration` | float64 | Recording length in seconds. |
| `prompt_level` | int64 | Difficulty of the original prompt: 1 (easy), 2 (medium), 3 (hard). |

Audio is included directly in the Parquet files.

## Collection

Knäck Klang invited participants to challenge Klang's Swedish speech recognition: the more transcription errors, the higher their score. Participants joined mainly through social media and could compare the transcription with the sentences on screen.

The challenge used a bank of **111 prompts**, ranging from everyday language to longer constructions and tongue-twisters. Each participant read one randomly selected prompt at each of three difficulty levels.

The collection took place during the first half of 2026. Contributors opted in to an open speech dataset through the collection website. Geographic coverage is strongest in southern Sweden, with contributions from across the country.

## Reference quality

Participants sometimes skipped or replaced words as they read. The Klang Research Team prepared the references from the recordings so that these changes would not be counted as recognition errors.

The team compared transcripts from multiple ASR models with the prompts and used alignment checks to identify discrepancies. The team manually reviewed roughly **1,000 recordings**, confirming or correcting references by listening. References were also accepted automatically when multiple ASR models agreed with the prompt and passed the quality checks.

The final dataset contains **259 distinct reference texts in `sv-clean`** and **319 in `sv-raw`**. In `sv-clean`, **203 recordings have references that differ from their assigned prompt**. Examples include:

| Sentence on screen | Reviewed transcript |
|---|---|
| Jag glömde köpa mjölk kan du svänga förbi **butiken**? | Jag glömde köpa mjölk kan du svänga förbi **affären**? |
| Vi såg en riktigt bra film **på bio** förra veckan. | Vi såg en riktigt bra film förra veckan. |

In the second example, an accurate transcription would score 20% WER against the ten-word prompt because the speaker omitted two words.

## License and contact

The dataset is available under **[Creative Commons Attribution 4.0 International](LICENSE)**.

For questions, corrections, or a recording removal request, [contact Klang](https://klang.ai/contact).

## Citation

Collected and maintained by the Research team at Klang.

```bibtex
@misc{klang_dialects_2026,
  author = {{Klang}},
  title = {Klang Dialects},
  year = {2026},
  url = {https://huggingface.co/datasets/KlangAI/klang-dialects}
}
```