Datasets:
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---
license: cc-by-nc-sa-4.0
task_categories:
- question-answering
language:
- ar
- en
tags:
- question-answering
- cultural-aligned
pretty_name: 'SpokenNativQA: Multilingual Everyday Spoken Queries for LLMs'
size_categories:
- 10K<n<100K
dataset_info:
- config_name: Arabic-ASR-Azure
splits:
- name: test
num_examples: 988
- config_name: Arabic-ASR-Whisper
splits:
- name: test
num_examples: 985
- config_name: Arabic-ASR-Fanar-Aura
splits:
- name: test
num_examples: 988
- config_name: Arabic-ASR-Google
splits:
- name: test
num_examples: 985
- config_name: English-ASR-Azure
splits:
- name: test
num_examples: 2322
- config_name: English-ASR-Whisper
splits:
- name: test
num_examples: 2322
- config_name: English-ASR-Fanar-Aura
splits:
- name: test
num_examples: 2322
- config_name: English-ASR-Google
splits:
- name: test
num_examples: 2322
configs:
- config_name: Arabic-ASR-Azure
data_files:
- split: test
path: arabic_qa/spokenqa_arabic_qa_test_azure_asr.json
- config_name: Arabic-ASR-Whisper
data_files:
- split: test
path: arabic_qa/spokenqa_arabic_qa_test_whisper_asr.json
- config_name: Arabic-ASR-Fanar-Aura
data_files:
- split: test
path: arabic_qa/spokenqa_arabic_qa_test_fanar_asr.json
- config_name: Arabic-ASR-Google
data_files:
- split: test
path: arabic_qa/spokenqa_arabic_qa_test_google_asr.json
- config_name: English-ASR-Azure
data_files:
- split: test
path: english_qa/spokenqa_english_qa_test_azure_asr.json
- config_name: English-ASR-Whisper
data_files:
- split: test
path: english_qa/spokenqa_english_qa_test_whisper_asr.json
- config_name: English-ASR-Fanar-Aura
data_files:
- split: test
path: english_qa/spokenqa_english_qa_test_fanar_asr.json
- config_name: English-ASR-Google
data_files:
- split: test
path: english_qa/spokenqa_english_qa_test_google_asr.json
---
# SpokenNativQA: Multilingual Everyday Spoken Queries for LLMs
The [**SpokenNativQA**]() dataset consists of question-answer (QA) pairs, where queries are sourced from real users and answers are manually reviewed and edited. The dataset covers a diverse range of 18 topics that reflect culturally and regionally specific knowledge, as well as everyday queries. These topics include animals, business, clothing, education, events, food and drinks, general knowledge, geography, immigration, language, literature, names and persons, plants, religion, sports and games, tradition, travel, and weather.
SpokenNativQA provides **multilingual test sets of everyday spoken questions** to evaluate large language models (LLMs) and speech processing systems. The dataset contains **Arabic** and **English** queries, each transcribed by multiple automatic speech recognition (ASR) systems.
<p align="left"> <img src="./spokennativqa.png" style="width: 60%;" id="title-icon"> </p>
**<span style="color:blue">Note:</span>** As a part of this repository we only shared the wav files that are only used for evaluation. For the entire dataset that we reported in the paper might be accessible after contacting with the authors.
## Directory Overview
The dataset is organized into two main directories:
- **`arabic_qa/`**
- `spokenqa_arabic_qa_test_azure_asr.jsonl`
- `spokenqa_arabic_qa_test_fanar_asr.jsonl`
- `spokenqa_arabic_qa_test_google_asr.jsonl`
- `spokenqa_arabic_qa_test_whisper_asr.jsonl`
- `spokenqa_arabic_qa_test.jsonl`
- `speech/` -- wav files
- **`english_qa/`**
- `spokenqa_english_qa_test_azure_asr.jsonl`
- `spokenqa_english_qa_test_fanar_asr.jsonl`
- `spokenqa_english_qa_test_google_asr.jsonl`
- `spokenqa_english_qa_test.jsonl`
- `speech/` -- wav files
### Dataset Structure and Format
Each `.jsonl` file contains a list of JSON objects, one per line. The typical structure includes:
- **`lang`**: The language of the spoken query (e.g., "arabic", "english").
- **`data_id`**: A unique identifier for the data instance.
- **`file_name`**: The name of the audio file.
- **`file_path`**: The relative path of the audio file.
- **`question`**: The intended question in text form (reference).
- **`answer`**: The expected answer or reference answer for the question.
- **`location`**: The geographical location where the query was recorded.
- **`asr_text`**: The text output from the ASR system.
### Example of a JSON Entry
```json
{
"lang": "arabic",
"data_id": "3cdfcfd1acb722617ec8bbe6808114bc",
"file_name": "3cdfcfd1acb722617ec8bbe6808114bc_1724222501325.wav",
"file_path": "speech/3cdfcfd1acb722617ec8bbe6808114bc_1724222501325.wav",
"question": "من هو الشاعر الذي سجن؟",
"answer": "وهي القصائد التي كتبها أبو فراس الحمداني فترة أسره عند الروم في سجن خرشنة، وعرفت باسم الروميات نسبة لمكان أسره، وقد تميزت هذا القصائد بجزالتها وقوتها ورصانتها، وصدق عاطفتها.",
"location": "qatar",
"asr_text": "من هو الشاعر الذي زعل؟"
}
```
# Experimental Scripts:
All of the experimental scripts are available as a part of [https://github.com/qcri/LLMeBench](https://github.com/qcri/LLMeBench) framework.
# License
This dataset is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
# Citation
If you are using this dataset in your research, we kindly ask that you cite our [paper](https://www.arxiv.org/pdf/2505.19163).
```
@inproceedings{alam2025spokennativqa,
title = {SpokenNativQA: Multilingual Everyday Spoken Queries for LLMs},
author = {Firoj Alam and Md Arid Hasan and Shammur Absar Chowdhury},
booktitle = {Proceedings of the 26th Interspeech Conference (Interspeech 2025)},
year = {2025},
address = {Rotterdam, The Netherlands},
month = aug,
organization = {ISCA},
}
```
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