Sub-Saharan Africa · Ge'ez (Ethiopic)
Amharic Voice Assistant Dataset
Amharic 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 Amharic is its own problem
Amharic voice-assistant data has a problem that is not about language at all: time. Ethiopia runs its own calendar and a twelve-hour clock that starts six hours before the conventional one, so a user who says three o'clock means something a system expecting international time will get wrong. The intent schema has to fix how date and time expressions are normalized before a single utterance is recorded, and honorific and plain ways of addressing the device both occur.
The field to pin down first: The intent schema must state the clock and calendar convention it normalizes to, and whether honorific and plain address forms are merged into one intent or kept apart with their own examples.
At a glance
| Language | Amharic |
|---|---|
| Primary region | Sub-Saharan Africa |
| Writing system | Ge'ez (Ethiopic) |
| Category | Voice Assistant |
| Specification field to settle first | The intent schema must state the clock and calendar convention it normalizes to, and whether honorific and plain address forms are merged into one intent or kept apart with their own examples. |
| 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 Amharic demands
Amharic uses the Ge'ez (Ethiopic) script, in which each consonant has seven vowel-variant glyphs. Which variant is written and how the sound is actually pronounced in speech often disagree, so the annotation guideline has to state which side governs.
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 Amharic Voice Assistant
How many distinct speakers can you provide for Amharic 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 state the clock and calendar convention it normalizes to, and whether honorific and plain address forms are merged into one intent or kept apart with their own examples.
Can you annotate to our own guideline instead of the default?
Yes, and for this pairing we would recommend it. Amharic voice-assistant data has a problem that is not about language at all: time. 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 Amharic 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 Amharic
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Amharic In-the-Wild Speech
Speech collected under fully natural conditions — no studio, no topic constraints — as close to real usage as collection gets.
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Amharic Call Center Speech
Recorded customer-service calls, real or simulated, capturing both the agent and the caller side, used for call center QC, intent recognition, and dialogue systems.
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Amharic Conversational Speech
Speech from natural conversation between two or more people, on open or semi-structured topics, used for conversational AI, voice assistants, and small talk models.
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Amharic Singing Voice
Vocal recordings with melody, in both a cappella and accompanied form, used for singing voice synthesis, music information retrieval, and lyric alignment.
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Amharic Speech Commands
Targeted recordings of short command words or phrases, usually with many speakers reading each entry several times over, used for wake words and on-device command recognition.
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Amharic Read Speech
Recordings of speakers reading specified text, with clear pronunciation and known text, the base material for TTS and ASR.
Voice Assistant in other languages
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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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Indonesian Voice Assistant
Southeast Asia
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Thai Voice Assistant
Southeast Asia
Request Amharic 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.