Datasets:
File size: 26,832 Bytes
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---
dataset_info:
- config_name: Bulgarian
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Czech
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Danish
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: German
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Greek
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: English
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- config_name: Spanish
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Estonian
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Finnish
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: French
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Croatian
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Hungarian
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Italian
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Lithuanian
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Latvian
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Dutch
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Polish
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Portuguese
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Romanian
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Russian
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Slovak
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Swedish
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: Ukrainian
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
- config_name: All
features:
- dtype: string
name: utt_id
- dtype:
audio:
sampling_rate: 16000
name: audio
- dtype: float64
name: duration
- dtype: string
name: lang
- dtype: string
name: task
- dtype: string
name: text
- dtype: string
name: translation_en
- dtype: string
name: original_audio_id
- dtype: float64
name: original_audio_offset
splits:
- name: asr_only
- name: ast
configs:
- config_name: Bulgarian
data_files:
- path: data/bg*/asr_only/*.parquet
split: asr_only
- path: data/bg*/ast/*.parquet
split: ast
- config_name: Czech
data_files:
- path: data/cs*/asr_only/*.parquet
split: asr_only
- path: data/cs*/ast/*.parquet
split: ast
- config_name: Danish
data_files:
- path: data/da*/asr_only/*.parquet
split: asr_only
- path: data/da*/ast/*.parquet
split: ast
- config_name: German
data_files:
- path: data/de*/asr_only/*.parquet
split: asr_only
- path: data/de*/ast/*.parquet
split: ast
- config_name: Greek
data_files:
- path: data/el*/asr_only/*.parquet
split: asr_only
- path: data/el*/ast/*.parquet
split: ast
- config_name: English
data_files:
- path: data/en*/asr_only/*.parquet
split: asr_only
- config_name: Spanish
data_files:
- path: data/es*/asr_only/*.parquet
split: asr_only
- path: data/es*/ast/*.parquet
split: ast
- config_name: Estonian
data_files:
- path: data/et*/asr_only/*.parquet
split: asr_only
- path: data/et*/ast/*.parquet
split: ast
- config_name: Finnish
data_files:
- path: data/fi*/asr_only/*.parquet
split: asr_only
- path: data/fi*/ast/*.parquet
split: ast
- config_name: French
data_files:
- path: data/fr*/asr_only/*.parquet
split: asr_only
- path: data/fr*/ast/*.parquet
split: ast
- config_name: Croatian
data_files:
- path: data/hr*/asr_only/*.parquet
split: asr_only
- path: data/hr*/ast/*.parquet
split: ast
- config_name: Hungarian
data_files:
- path: data/hu*/asr_only/*.parquet
split: asr_only
- path: data/hu*/ast/*.parquet
split: ast
- config_name: Italian
data_files:
- path: data/it*/asr_only/*.parquet
split: asr_only
- path: data/it*/ast/*.parquet
split: ast
- config_name: Lithuanian
data_files:
- path: data/lt*/asr_only/*.parquet
split: asr_only
- path: data/lt*/ast/*.parquet
split: ast
- config_name: Latvian
data_files:
- path: data/lv*/asr_only/*.parquet
split: asr_only
- path: data/lv*/ast/*.parquet
split: ast
- config_name: Dutch
data_files:
- path: data/nl*/asr_only/*.parquet
split: asr_only
- path: data/nl*/ast/*.parquet
split: ast
- config_name: Polish
data_files:
- path: data/pl*/asr_only/*.parquet
split: asr_only
- path: data/pl*/ast/*.parquet
split: ast
- config_name: Portuguese
data_files:
- path: data/pt*/asr_only/*.parquet
split: asr_only
- path: data/pt*/ast/*.parquet
split: ast
- config_name: Romanian
data_files:
- path: data/ro*/asr_only/*.parquet
split: asr_only
- path: data/ro*/ast/*.parquet
split: ast
- config_name: Russian
data_files:
- path: data/ru*/asr_only/*.parquet
split: asr_only
- path: data/ru*/ast/*.parquet
split: ast
- config_name: Slovak
data_files:
- path: data/sk*/asr_only/*.parquet
split: asr_only
- path: data/sk*/ast/*.parquet
split: ast
- config_name: Swedish
data_files:
- path: data/sv*/asr_only/*.parquet
split: asr_only
- path: data/sv*/ast/*.parquet
split: ast
- config_name: Ukrainian
data_files:
- path: data/uk*/asr_only/*.parquet
split: asr_only
- path: data/uk*/ast/*.parquet
split: ast
- config_name: All
default: true
data_files:
- path: data/*/asr_only/*.parquet
split: asr_only
- path: data/*/ast/*.parquet
split: ast
license: cc-by-3.0
task_categories:
- automatic-speech-recognition
- translation
language:
- bg
- cs
- da
- de
- el
- en
- es
- et
- fi
- fr
- hr
- hu
- it
- lt
- lv
- nl
- pl
- pt
- ro
- ru
- sk
- sv
- uk
pretty_name: YODAS-Granary
size_categories:
- 10M<n<100M
---
## Table of Contents
- [Dataset Description](#dataset-description)
- [Overview](#overview)
- [Data Distribution](#data-distribution)
- [How to Use](#how-to-use)
- [Standard Loading](#standard-loading)
- [Streaming](#streaming)
- [Dataset Structure](#dataset-structure)
- [Data Instance](#data-instance)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Reference](#reference)
# Dataset Card for YODAS-Granary
- **Repository:** [NeMo-speech-data-processor: Granary](https://github.com/NVIDIA/NeMo-speech-data-processor/tree/main/dataset_configs/multilingual/granary)
- **Paper:** [Granary: Speech Recognition and Translation Dataset in 25 European Languages](https://arxiv.org/abs/2505.13404)
- **Shared by:** [ESPnet](https://huggingface.co/espnet)
## Dataset Description
YODAS-Granary is a curated subset of the larger [`nvidia/Granary`](https://huggingface.co/datasets/nvidia/Granary) dataset, focusing on high-quality pseudo-labeled speech data for Automatic Speech Recognition (ASR) and Automatic Speech Translation (AST) across 23 European languages.
### Overview
<table style="width:100%; table-layout:auto;">
<tr>
<td style="vertical-align:middle; text-align:center;">
<img src="./scheme.png" style="max-width:100%;">
</td>
<td style="vertical-align:middle; padding-left:20px;">
<p>
Derived from the <a href=https://huggingface.co/datasets/espnet/yodas2) target="_blank"><code>espnet/yodas2</code></a> corpus, YODAS-Granary provides high-quality pseudo-labeled speech data, focusing on two core tasks:
</p>
<ul>
<li><strong>Automatic Speech Recognition (ASR)</strong>: covers 23 European languages, with pseudo-labeled transcriptions generated using the <a href="https://huggingface.co/Systran/faster-whisper-large-v3" target="_blank"><code>Systran/faster-whisper-large-v3</code></a> model, post-processed to restore punctuation and capitalization using <a href="https://huggingface.co/Qwen/Qwen2.5-7B-Instruct" target="_blank"><code>Qwen/Qwen2.5-7B-Instruct</code></a>, and filtered for quality.</li>
<li><strong>Automatic Speech Translation (AST)</strong>: covers 22 non-English languages and consists of high-quality translations into English, generated from <code>ASR</code> subset using the <a href="https://huggingface.co/utter-project/EuroLLM-9B-Instruct" target="_blank"><code>utter-project/EuroLLM-9B-Instruct</code></a> model and filtered for quality.</li>
</ul>
</td>
</tr>
</table>
### Data Distribution
The following chart illustrates the distribution of data in the YODAS-Granary dataset across 23 European languages, measured in number of words (left) and total hours of audio (right), for both ASR and AST tasks.
<p align="center">
<img src="./chart.png" width="100%"/><br>
<em>🔍 AST data is always a filtered subset of ASR, which is why AST bars are never taller than their ASR counterparts.<br>🗣️ The English subset contains ASR data only.</em>
</p>
The table below summarizes the storage footprint and sample counts per language in the YODAS-Granary dataset, broken down into corresponding [splits](#data-splits):
- `ast` — the size and number of translated samples (X → English),
- `asr_only` — samples that exist only in the ASR subset and have no corresponding translation,
and combined size and number of all samples per language (`total`).
| Language | Subsets | Samples [`ast`] | Size [`ast`] | Samples [`asr_only`] | Size [`asr_only`] | Total samples | Total size |
|:----------:|:----------------------------:|:---------------:|:------------:|:--------------------:|:-----------------:|:---------------:|:------------:|
| Bulgarian | `bg000` | 8844 | 1.9 GB | 1533 | 208.8 MB | 10377 | 2.1 GB |
| Czech | `cs000` | 34360 | 7.5 GB | 4185 | 442.1 MB | 38545 | 8.0 GB |
| Danish | `da000` | 9582 | 1.9 GB | 656 | 65.3 MB | 10238 | 2.0 GB |
| German | `de000`, `de{100..102}` | 3335156 | 845.6 GB | 415260 | 56.3 GB | 3750416 | 901.9 GB |
| Greek | `el000` | 4242 | 1.6 GB | 514 | 113.5 MB | 4756 | 1.7 GB |
| English | `en00{0..7}`, `en{100..129}` | ❌ | ❌ | 40810517 | 11.3 TB | 40810517 | 11.3 TB |
| Spanish | `es000`, `es{100..108}` | 7923646 | 2.9 TB | 951450 | 88.8 GB | 8875096 | 3.0 TB |
| Estonian | `et000` | 4437 | 901.8 MB | 513 | 57.8 MB | 4950 | 959.6 MB |
| Finnish | `fi000` | 60729 | 17.4 GB | 4637 | 419.3 MB | 65366 | 17.8 GB |
| French | `fr000`, `fr{100..103}` | 4766239 | 1.3 TB | 558848 | 81.1 GB | 5325087 | 1.4 TB |
| Croatian | `hr000` | 5369 | 1.1 GB | 261 | 27.9 MB | 5630 | 1.1 GB |
| Hungarian | `hu000` | 48263 | 16.4 GB | 6530 | 962.7 MB | 54793 | 17.4 GB |
| Italian | `it000`, `it{100..101}` | 1226663 | 683.7 GB | 86587 | 13.6 GB | 1313250 | 697.3 GB |
| Lithuanian | `lt000` | 2177 | 564.5 MB | 390 | 71.1 MB | 2567 | 635.6 MB |
| Latvian | `lv000` | 272 | 66.5 MB | 75 | 12.0 MB | 347 | 78.5 MB |
| Dutch | `nl000`, `nl100` | 865754 | 151.1 GB | 71490 | 4.3 GB | 937244 | 155.4 GB |
| Polish | `pl000` | 264257 | 75.5 GB | 28678 | 2.4 GB | 292935 | 77.9 GB |
| Portuguese | `pt000`, `pt{100..103}` | 5898764 | 1.5 TB | 729138 | 30.1 GB | 6627902 | 1.5 TB |
| Romanian | `ro000` | 12276 | 3.7 GB | 2303 | 663.4 MB | 14579 | 4.4 GB |
| Russian | `ru00{0..1}`, `ru{100..106}` | 7991038 | 2.1 TB | 1876876 | 197.0 GB | 9867914 | 2.3 TB |
| Slovak | `sk000` | 3405 | 992.0 MB | 287 | 51.9 MB | 3692 | 1.0 GB |
| Swedish | `sv000` | 54085 | 10.2 GB | 3192 | 215.7 MB | 57277 | 10.4 GB |
| Ukrainian | `uk000`, `uk100` | 246373 | 68.3 GB | 9479 | 1.2 GB | 255852 | 69.4 GB |
***
## How to use
### Standard Loading
You can load the dataset using the `datasets` library from Hugging Face:
```python
from datasets import load_dataset
```
**🔹 Load the entire dataset:**
```python
ds = load_dataset("espnet/yodas-granary")
```
**🔹 Load a single language (e.g., Italian):**
```python
ds = load_dataset("espnet/yodas-granary", "Italian")
```
### Streaming
Some language subsets are quite large and may not fit comfortably in memory. For efficient access and analysis without downloading the entire dataset, we recommend using streaming mode:
``` python
ds = load_dataset("espnet/yodas-granary", "English", streaming=True)
```
## Dataset Structure
### Data Instance
Each utterance in the dataset includes the following fields: `utt_id`, `audio`, `duration`, `lang`, `task`, `text`, `translation_en` (`null` in `asr_only`), `original_audio_id`, and `original_audio_offset`.
**Typical entry**
from `data/de101/translation/00000000.parquet`
```python
{
"utt_id": "de101_00000000_Z0_gcPJVTqg_1004_62_1_74",
"audio": {
'path': 'de101_00000000_Z0_gcPJVTqg_1004_62_1_74.wav',
'bytes': ...
}
"duration": 1.74,
"lang": "<de>",
"task": "<ast>",
"text": "Ich muss mir das Zeug mal aus der Nähe ansehen.",
"translation_en": "I have to take a closer look at this stuff.",
"original_audio_id": "Z0_gcPJVTqg",
"original_audio_offset": 1004.62
}
```
### Data Fields
| **Field** | **Type** | **Description** |
|---|---|---|
| `utt_id¹` | `string` | Unique identifier of the utterance, referencing the original segment. |
| `audio` | `Audio (16 kHz)` | Audio data of the utterance, stored as PCM waveform. |
| `duration` | `float64` | Duration of the utterance in seconds. |
| `lang` | `string` | Language of the utterance, in ISO 639-1 code (e.g., `<de>` for German). |
| `task` | `string` | Task type: either `<asr>` for transcription or `<ast>` for translation to English. |
| `text` | `string` | Transcription of the utterance in its original language. |
| `translation_en` | `string` | English translation of the utterance. `null` if split is `asr_only`. |
| `original_audio_id` | `string` | ID of the original audio file. This value corresponds to the `audio_id` field from the [`espnet/yodas2`](https://huggingface.co/datasets/espnet/yodas2) dataset. |
| `original_audio_offset` | `float64` | Start time (in seconds) of the utterance within the original audio file. |
¹ - `utt_id` is encoded as `<subset>_<shard>_<wav_id>_<start_time_s>_<start_time_decimals>_<duration_s>_<duration_decimals>`, where `subset`, `shard²`, and `wav_id` match the utterance's location in the original [`espnet/yodas2`](https://huggingface.co/datasets/espnet/yodas2) archive.
² - `shard` indices reflect those in [`espnet/yodas2`](https://huggingface.co/datasets/espnet/yodas2), but some shards are missing due to filtering during data processing. In particular, `bg000` is missing shard `00000011`, `en000` is missing shard `00000308`, `en003` is missing shard `00000221`, `en118` is missing shard `00000240`.
### Data Splits
The dataset is organized into language-specific subsets, each containing one or two splits, depending on the language:
- **For non-English languages:**
- `<ast>` – samples with **both high-quality transcriptions and translations** into English.
- `<asr_only>` – samples that passed transcription quality checks but do not include translations.
- **For `English`**:
- `<asr_only>` split is available only, since English-to-English translation is not applicable.
**Directory example**
``` python
yodas_granary
└── data
├── da000 # subset
│ ├── asr_only # corresponds to `asr_only` split
│ │ ├── 00000000.parquet # shard
│ │ ├── 00000001.parquet
│ │ ├── 00000002.parquet
│ │ └── ...
│ └── ast # corresponds to `ast` split
│ ├── 00000000.parquet # shard
│ ├── 00000001.parquet
│ ├── 00000002.parquet
│ └── ...
├── cs000
├── bg000
└── ...
```
***
## Reference
```bibtex
@misc{koluguri2025granaryspeechrecognitiontranslation,
title={Granary: Speech Recognition and Translation Dataset in 25 European Languages},
author={Nithin Rao Koluguri and Monica Sekoyan and George Zelenfroynd and Sasha Meister and Shuoyang Ding and Sofia Kostandian and He Huang and Nikolay Karpov and Jagadeesh Balam and Vitaly Lavrukhin and Yifan Peng and Sara Papi and Marco Gaido and Alessio Brutti and Boris Ginsburg},
year={2025},
eprint={2505.13404},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2505.13404},
}
``` |