Southeast Asia · Latin
Indonesian Voice Assistant Dataset
Indonesian voice assistant sourced to your specification — no inventory, no fixed listing. This page covers what is specifically hard about this pairing, and which fields your specification needs to pin down.
Why voice assistant in Indonesian is its own problem
Intent annotation for Indonesian voice assistants has to handle three-way mixing — a user may express the same intent in Indonesian, in a regional language, or in English. Without normalization in the intent schema, one intent splits into three classes.
The field to pin down first: The intent schema must normalize across languages and provide the mapping between the expressions used in each.
At a glance
| Language | Indonesian |
|---|---|
| Primary region | Southeast Asia |
| Writing system | Latin |
| Category | Voice Assistant |
| Specification field to settle first | The intent schema must normalize across languages and provide the mapping between the expressions used in each. |
| Delivery | Sourced to order, pilot batch before the full run |
What voice assistant data is
Command and dialogue data for voice assistants, usually with intent annotation, covering the full chain from wake word to understanding to response.
What buyers get wrong about it
What buyers actually need is intent plus slot annotation, not just audio and transcription. The intent taxonomy has to align with the schema the buyer already runs.
The specification field that decides the quote
Whether the intent schema comes from the buyer or is designed by us — this is the dividing line in the quote.
The language side: what Indonesian demands
In everyday speech, Indonesians mix in local languages (Javanese, Sundanese) and English loanwords heavily. Three language components inside a single sentence is normal, so word segmentation and annotation rules have to be fixed before collection begins.
What we can put in this delivery
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Read and conversational speech
Scripted recording for TTS, and unscripted conversation for recognition. Specified separately because they need different speaker pools.
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Transcription to your convention
Orthographic or phonetic, with the guideline written before production and shared with you for review.
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Speaker metadata
Age band, gender, region and dialect background per file, so you can slice the dataset rather than take it whole.
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Consent documentation
Signed speaker consent covering the intended use, plus collection methodology and the annotation guideline.
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Pilot batch
A small batch first, which you can reject. Misalignments surface after a few hours rather than at delivery.
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Delivery in your format
Audio format, sampling rate, segmentation length and metadata schema set to your pipeline's requirements.
What arrives in a delivery
| Component | What it is |
|---|---|
| Audio files | Format, sampling rate and segmentation length set to your pipeline. Named to a convention you specify. |
| Transcription | Orthographic or phonetic, produced under a guideline you review before production starts. |
| Speaker metadata | Age band, gender, region and dialect background per file, plus a speaker identifier so the dataset can be sliced. |
| Recording conditions | Environment, device and, where relevant, measured signal-to-noise ratio per file. |
| Annotation guideline | The document the annotators worked from, so you can reproduce the conventions on your own data. |
| Consent records | Signed speaker consent covering your intended use, with the transfer mechanism addressed where required. |
| Collection methodology | How speakers were recruited, screened and scheduled — the part that tells you how biased the pool is. |
| Quality report | Pilot outcome, re-work log, and the annotator agreement figures where the task supports measuring them. |
Questions we get about Indonesian Voice Assistant
How many distinct speakers can you provide for Indonesian Voice Assistant?
It depends on the specification and the timeline, and we will give a real number rather than a target. For this pairing, speaker recruitment is usually the step that sets the schedule. The intent schema must normalize across languages and provide the mapping between the expressions used in each.
Can you annotate to our own guideline instead of the default?
Yes, and for this pairing we would recommend it. Intent annotation for Indonesian voice assistants has to handle three-way mixing — a user may express the same intent in Indonesian, in a regional language, or in English. That is exactly the kind of decision a default guideline leaves open, and it is where annotators diverge. Send us your guideline, or we will draft one and you can review it before production starts.
Do you offer a sample before we commit to a full run?
Yes. Select a free sample in the request form and describe what you need. A pilot batch is the cheapest way to establish whether the quality bar is reachable for Indonesian Voice Assistant before committing to the full volume.
Is the data licensed or owned outright?
Licensing terms are set per project, so tell us how the model will be used and whether it will be distributed. Consent documentation travels with the data either way, and we do not handle medical or clinical data or recorded telephone calls.
Other datasets in Indonesian
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Indonesian Audiobook
Continuous long-form narration in audiobook style, steady in intonation and generous in duration, the main source material for high-quality TTS.
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Indonesian Short Video Speech
Speech in the talking-head style of short video — fast, emotionally strong, colloquial — used for short video subtitles and content understanding.
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Indonesian Live Stream Speech
Long-session spoken content from live streams — host monologue and responses to audience interaction — fast-paced and heavily improvised.
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Indonesian Elderly Voice
Speech data from elderly speakers, usually stratified by age band and health status, used for voice products built for older users.
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Indonesian Accented English
English speech from non-native speakers or specific regional accents, grouped by accent origin, used to improve accent robustness in ASR.
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Indonesian Speech Translation
Parallel data pairing source-language audio with target-language translation, used for speech-to-text and speech-to-speech translation models.
Voice Assistant in other languages
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Kurdish Voice Assistant
Middle East & North Africa
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Hausa Voice Assistant
Sub-Saharan Africa
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Uzbek Voice Assistant
Central Asia & Caucasus
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Hindi Voice Assistant
South Asia
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Arabic (MSA) Voice Assistant
Middle East & North Africa
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Thai Voice Assistant
Southeast Asia
Request Indonesian Voice Assistant
Tell us the language, the hours, and what the data needs to look like. You will get a real number and a real timeline — not a range. If we cannot source it well, we will tell you that instead.
- Pilot batch before the full run, so problems surface early.
- Consent documentation delivered with the data.
- No medical or clinical data. No recorded telephone calls.