text_prompt stringlengths 7 356 | audio_prompt_female_1 audioduration (s) 0.91 29.5 ⌀ | audio_prompt_female_2 audioduration (s) 1.79 20.8 ⌀ | audio_prompt_male_1 audioduration (s) 1.43 28.9 ⌀ | audio_prompt_male_2 audioduration (s) 1.18 34.1 ⌀ | language stringclasses 12 values | task stringclasses 11 values | prompt_type stringclasses 5 values |
|---|---|---|---|---|---|---|---|
Please transcribe the clip. | en | asr | basic | ||||
Convert the spoken content into text. | en | asr | basic | ||||
Please transcribe the recorded content into a written format. | en | asr | formal | ||||
Kindly produce an accurate textual transcription of this recording. | en | asr | formal | ||||
Hey, can you write out what's being said in this audio? | en | asr | informal | ||||
Please jot down everything you hear in this clip. | en | asr | informal | ||||
Please listen to the entire audio clip and provide a complete, accurate transcription of all spoken words. | en | asr | detailed | ||||
Kindly convert the full spoken content of this recording into a clear and precise text transcript. | en | asr | detailed | ||||
Please transcribe. | en | asr | short | ||||
Transcribe this clip. | en | asr | short | ||||
Please translate the recording into English. | en | st | basic | ||||
Convert the conversation into English. | en | st | basic | ||||
Please translate the audio content into English with high accuracy. | en | st | formal | ||||
Kindly provide a precise translation into English. | en | st | formal | ||||
Hey, can you translate what they're saying into English? | en | st | informal | ||||
Please turn this audio into English for me. | en | st | informal | ||||
Please listen to the full audio file and provide a complete, accurate translation of all spoken content into English. | en | st | detailed | ||||
Kindly convert the entire spoken content of this recording into a clear and faithful English translation, preserving meaning and tone. | en | st | detailed | ||||
Translate into English. | en | st | short | ||||
In English, please. | en | st | short | ||||
Please answer the question based on the clip: <question>. | en | sqa | basic | ||||
Listen to the recording and provide the answer to: <question>. | en | sqa | basic | ||||
Kindly listen to the provided recording and supply an accurate answer to the following question: <question>. | en | sqa | formal | ||||
Please analyze the audio content and deliver a precise response to the question: <question>. | en | sqa | formal | ||||
Hey, can you listen to this and tell me the answer to <question>? | en | sqa | informal | ||||
Give the clip a listen and let me know the answer to this: <question>. | en | sqa | informal | ||||
Please carefully listen to the entire audio clip and provide a complete and context-aware answer to the question: <question>. | en | sqa | detailed | ||||
Using all relevant information from the recording, deliver a clear and well-reasoned answer to this question: <question>. | en | sqa | detailed | ||||
What is the answer: <question>. | en | sqa | short | ||||
Listen and answer: <question>. | en | sqa | short | ||||
Please summarize the recording. | en | ssum | basic | ||||
Provide a brief summary of the content. | en | ssum | basic | ||||
Kindly listen to this and produce a concise and accurate summary. | en | ssum | formal | ||||
Please generate a well-structured summary of the audio clip. | en | ssum | formal | ||||
Hey, can you listen to this and tell me the main points? | en | ssum | informal | ||||
Give this clip a listen and sum it up for me. | en | ssum | informal | ||||
Please listen to the full recording and provide a comprehensive summary capturing all key ideas, themes, and important details. | en | ssum | detailed | ||||
Create a clear, well-organized summary of the recording, highlighting major points, supporting information, and any conclusions mentioned. | en | ssum | detailed | ||||
Summarize. | en | ssum | short | ||||
Give a short summary. | en | ssum | short | ||||
Please interpret the meaning of the spoken clip. | en | slu | basic | ||||
Extract the intent and key information from this recording. | en | slu | basic | ||||
Kindly analyze the spoken content and provide the detected intent along with relevant entities. | en | slu | formal | ||||
Please perform spoken language understanding on this recording and produce its semantic interpretation. | en | slu | formal | ||||
Hey, can you figure out what the speaker wants from this clip? | en | slu | informal | ||||
Listen to this and tell me the intent and important details. | en | slu | informal | ||||
Please listen to the complete recording and provide a full semantic interpretation, including intent, key entities, and any relevant contextual information. | en | slu | detailed | ||||
Analyze the recording and deliver a structured SLU output that captures the speaker's intent, slots, entities, and any additional semantic cues. | en | slu | detailed | ||||
Extract intent and entities. | en | slu | short | ||||
Do SLU on this audio. | en | slu | short | ||||
Please convert this text into speech. | en | tts | basic | ||||
Generate spoken audio from the following text. | en | tts | basic | ||||
Kindly produce a natural-sounding speech rendition of the provided text. | en | tts | formal | ||||
Please synthesize this text into clear and accurate audio output. | en | tts | formal | ||||
Hey, read this text out loud. | en | tts | informal | ||||
Generate speech from this. | en | tts | informal | ||||
Please convert the entire text into speech, maintaining proper intonation, pauses, and emphasis for a natural delivery. | en | tts | detailed | ||||
Generate a high-quality spoken version of the text, capturing nuances, punctuation, and expressive tone. | en | tts | detailed | ||||
Text to speech. | en | tts | short | ||||
Speak this text. | en | tts | short | ||||
Please translate this clip into English speech. | en | s2st | basic | ||||
Convert the spoken content into English audio. | en | s2st | basic | ||||
Kindly produce a spoken translation of this recording in English. | en | s2st | formal | ||||
Please generate an accurate English speech rendition of the provided recording. | en | s2st | formal | ||||
Hey, can you turn this into English audio? | en | s2st | informal | ||||
Make this clip speak in English. | en | s2st | informal | ||||
Please listen to the full recording and provide a natural, contextually accurate spoken translation in English, preserving tone and meaning. | en | s2st | detailed | ||||
Generate a high-quality English speech version of this recording, maintaining intonation, emphasis, and any expressive cues. | en | s2st | detailed | ||||
Translate to English speech. | en | s2st | short | ||||
S2ST: English. | en | s2st | short | ||||
Please translate the text to English. | en | mt | basic | ||||
Convert this text into English. | en | mt | basic | ||||
Kindly provide an accurate translation of the following text to English. | en | mt | formal | ||||
Please translate this text into English, preserving its meaning and tone. | en | mt | formal | ||||
Hey, can you translate this into English? | en | mt | informal | ||||
Turn this into English for me. | en | mt | informal | ||||
Please translate the full text to English, maintaining clarity, context, and natural phrasing. | en | mt | detailed | ||||
Provide a high-quality translation of this text, preserving idiomatic expressions and the intended meaning to English. | en | mt | detailed | ||||
Translate to English. | en | mt | short | ||||
MT: English. | en | mt | short | ||||
Please summarize the text. | en | tsum | basic | ||||
Provide a brief summary. | en | tsum | basic | ||||
Kindly generate a concise and accurate summary of the following text. | en | tsum | formal | ||||
Please produce a well-structured summary of the text. | en | tsum | formal | ||||
Hey, can you tell me the main points of this text? | en | tsum | informal | ||||
Give this a read and sum it up for me. | en | tsum | informal | ||||
Please create a comprehensive summary of the text, capturing all key ideas, supporting details, and conclusions. | en | tsum | detailed | ||||
Analyze the text and provide a detailed, well-organized summary highlighting major points and important information. | en | tsum | detailed | ||||
Summarize this. | en | tsum | short | ||||
Give a short summary. | en | tsum | short | ||||
Please transcribe the speech from the video. | en | lipread | basic | ||||
Write down what the person is saying in this video. | en | lipread | basic | ||||
Kindly provide an accurate transcription of the speech based on the speaker's lip movements in this video. | en | lipread | formal | ||||
Please analyze the video and generate a precise text transcription of the spoken content. | en | lipread | formal | ||||
Hey, can you tell me what they're saying by watching their lips? | en | lipread | informal | ||||
Watch this video and write down the words being spoken. | en | lipread | informal | ||||
Please carefully observe the speaker's lip movements throughout the video and provide a full and accurate transcription of all spoken words. | en | lipread | detailed | ||||
Generate a comprehensive text transcription based on the lip movements in the video, capturing every spoken word and context as accurately as possible. | en | lipread | detailed | ||||
Transcribe from lips. | en | lipread | short | ||||
Lipread and write. | en | lipread | short |
Do What I Say (DOWIS): A Spoken Prompt Dataset for Instruction-Following
NEW DOWIS now also contains spoken and written prompts in Albanian (sq), and for the tasks LIPREAD and SLU!
TL;DR — DOWIS is a multilingual dataset of human-recorded spoken and written instruction prompts, designed to enable realistic evaluation of Speech Large Language Models across 11 tasks and 12 languages.
Dataset Summary
Most Speech LLM benchmarks use text-based prompts, which does not reflect how users actually interact with these models in the real world. DOWIS fills this gap by providing human-recorded spoken prompts, paired with their written equivalents, across a wide range of tasks, languages, and prompt styles. Each prompt can be directly paired with any existing speech benchmark to evaluate how well Speech LLMs follow spoken instructions.
The dataset contains 1,320 rows, with up to 4 audio recordings per row (2 female, 2 male speakers where available), covering:
- 12 languages: cs, de, en, es, fr, hu, it, nl, pt, ru, sq, sv
- 11 tasks: ACHAP, ASR, MT, S2ST, SQA, SSUM, ST, TSUM, TTS, LIPREAD, SLU
- 5 prompt styles: basic, formal, informal, detailed, short
- 10 prompt variants per task-language pair
Details can be found in the corresponding paper on arXiv.
Code for benchmarking Speech LLMs with different task benchmarks coupled with DOWIS can be found on GitHub.
Tasks
| Task Code | Description |
|---|---|
| ACHAP | Audio Chaptering |
| ASR | Automatic Speech Recognition |
| MT | Machine Translation |
| S2ST | Speech-to-Speech Translation |
| SQA | Spoken Question Answering |
| SSUM | Speech Summarization |
| ST | Speech Translation |
| TSUM | Text Summarization |
| TTS | Text-to-Speech |
| LIPREAD | Lip-Reading |
| SLU | Spoken Language Understanding |
Prompt Styles
| Style | Description |
|---|---|
basic |
Natural, everyday phrasing a researcher would use |
formal |
Professional, polished language |
informal |
Conversational and casual |
detailed |
Explicit and precise instructions on how to perform the task |
short |
Concise as possible while remaining unambiguous |
Dataset Fields
| Field | Type | Description |
|---|---|---|
text_prompt |
string |
Written version of the instruction prompt |
audio_prompt_female_1 |
Audio |
Human-recorded female speaker (speaker 1), null if unavailable |
audio_prompt_female_2 |
Audio |
Human-recorded female speaker (speaker 2), null if unavailable |
audio_prompt_male_1 |
Audio |
Human-recorded male speaker (speaker 1), null if unavailable |
audio_prompt_male_2 |
Audio |
Human-recorded male speaker (speaker 2), null if unavailable |
language |
string |
ISO 639-1 language code (e.g. en, de) |
task |
string |
Task code the prompt is designed for (e.g. asr, mt) |
prompt_type |
string |
Prompt style: basic, formal, informal, detailed, or short |
Citation
If you use this work, please cite:
@misc{züfle2026isayspokenprompt,
title={Do What I Say: A Spoken Prompt Dataset for Instruction-Following},
author={Maike Züfle and
Sara Papi and
Fabian Retkowski and
Szymon Mazurek and
Marek Kasztelnik and
Alexander Waibel and
Luisa Bentivogli and
Jan Niehues},
year={2026},
eprint={2603.09881},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2603.09881}}
Dataset Contact: maike.zuefle@kit.edu
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