Meet 👋 Sahara,
Best-in-class speech recognition and text-to-speech models for African accents
Beats OpenAI, Google, AWS,
Azure across multiple benchmarks
- Meet
- Sahara
Speech Recognition That
Actually Gets African Accents
Trusted by Startups
and Enterprises
Medical
Here’s the kicker: we’re a tiny, seed-stage startup. We don’t have the luxury of bottomless compute or internet-scale data. So we had to do things differently — leaner, smarter, and relentlessly focused on real-world performance.
Mark White
Ceo of Company
Medical
Here’s the kicker: we’re a tiny, seed-stage startup. We don’t have the luxury of bottomless compute or internet-scale data. So we had to do things differently — leaner, smarter, and relentlessly focused on real-world performance.
Mark White
Ceo of Company
Medical
Here’s the kicker: we’re a tiny, seed-stage startup. We don’t have the luxury of bottomless compute or internet-scale data. So we had to do things differently — leaner, smarter, and relentlessly focused on real-world performance.
Mark White
Ceo of Company
Medical
Here’s the kicker: we’re a tiny, seed-stage startup. We don’t have the luxury of bottomless compute or internet-scale data. So we had to do things differently — leaner, smarter, and relentlessly focused on real-world performance.
Mark White
Ceo of Company
Benchmarks
Metric: Word Error Rate (WER), lower is better
Word Error Rate (WER) is a common way to measure how accurate speech recognition systems are. It compares what the system heard to what was actually said. It measures the model’s ERROR, so lower is better. It divides the number of word-level errors by the total number of words
A Quick Primer on Word Error Rate (WER)
What is WER?
Word Error Rate (WER) is a common way to measure how accurate speech recognition systems are. It compares what the system heard to what was actually said. It measures the model’s ERROR, so lower is better. It divides the number of word-level errors by the total number of words
Why it matters: WER tells us how reliable a speech-to-text system is. A lower WER means fewer mistakes and better performance—critical for areas like healthcare, legal, and customer service.
Strengths: Simple to calculate, Easy to compare different systems, Works across languages
Weaknesses: Treats all errors equally—even if some are more harmful (e.g., “don’t take” vs “take”); Even single character errors like carrot vs carot get full penalty, so it can be overly harsh and punitive; Doesn’t consider punctuation or context; May not reflect user satisfaction or usefulness
What is WER?
WER = (Substitutions +
Insertions + Deletions) ÷ Total Words
Substitutions: wrong words
Insertions: extra words
Deletions: missing words
Spoken: “Take your medicine daily”
Transcript: “Take your message daily”
WER = 1 error ÷ 4 words = 25%
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
Domains
Medical
Sahara demonstrates superior performance in accented voice recognition in healthcare, leading several open and closed models in recognition of complex medical terminologies across specialties, with various diagnosis, measurements, imaging and lab results, and medications in over 300 African accents under diverse ambient clinical settings
Datasets
Afrispeech-200 Clinical Test
a 200+hr public benchmark dataset of scripted (read) clinical speech in 120 African accents from 2,463 speakers in 13 countries
Afrispeech Dialog
a public pan-African conversational speech dataset of 49 spontaneous medical and non-medical conversations with 14 African accents across 3 countries
Hospital-Dictations-v1 (private)
a multi-institution multi-specialty dataset of real world medical speech in real-world clinical settings across 6 countries, 200+ speakers and >50 accents
Medical-Dictations-Noisy (private)
a multi-country dataset of real world doctors testing out voice transcription in various clinical settings with significant ambient hospital noise
Med-Convo-Nig
an unreleased medical multispecialty dataset of 25 simulated long-from doctor-patient conversations from male and female doctor- and patient actors across Nigeria
Focused-Group-Research-Interview (private)
an unreleased dataset of 30+ minute-long multispeaker clinical research interviews from East Africa
Call Center
Datasets
Call-Center (private)
an unreleased dataset of real-world telephone call center conversations between various agents and customers sampled at 8kHz.
Afri-Names-Commands
a 2hr subset with voice commands for multiple scenarios
Afri-Names-Numbers
a 2hr subset of the Afri-Names dataset rich in numbers, fractions, measurements, decimals, currency, etc
Named Entities
Datasets
Afri-Names
our most challenging dataset ever, a 20+ hour novel open pan-African accented read speech dataset rich with African named entities, proper nouns, numbers, fractions, currency, simulated IDs, and voice-assistant commands for evaluation ASR models on various tasks and domains like finance, healthcare, and speech commands, with 500+ unique speakers from 20+ countries.
African Names
a 10hr subset rich in African names
Voice Commands
a 5hr subset with voice commands for multiple scenarios
Numbers
a 5hr subset rich in numbers, fractions, measurements, decimals, currency, etc
Legal & Parliamentary
Datasets
Afrispeech-Parliamentary
a 35+ hour open pan-African transcribed dataset of legislative proceedings with ambient noise, multiple speakers, African names and locations, with over 1000 speakers from 4 countries
Legal-Court-Hearings (private)
an unreleased African accented dataset of court hearings rich in legal terminology, proper nouns and latin words
Country accent
Datasets
AfriSpeech-Countries
a multi-country multi-accent dataset with 2+ hrs of read/scripted and conversational speech from Nigeria, South Africa, Kenya, Ghana, Rwanda, and North Africa (Egypt, Morocco, Algeria, etc)
Meet the family
of models
intron-sahara-asr
general purpose cross-domain speech recognition model
intron-sahara-stream
streaming model optimised for medical conversations
intron-sahara-voice-lock
biometric voice-based authentication tuned for African accents and languages to combat fraud
intron-sahara-tts-en
first production pan-African accented speech synthesis model supporting 30 African accents spoken across 10+ countries
sahara-translate-preview
SOTA automatic speech translation models on 20 African languages
intron-sahara-asr
general purpose cross-domain speech recognition model
intron-sahara-stream
streaming model optimised for medical conversations
intron-sahara-voice-lock
biometric voice-based authentication tuned for African accents and languages to combat fraud
intron-sahara-tts-en
first production pan-African accented speech synthesis model supporting 30 African accents spoken across 10+ countries
sahara-translate-preview
SOTA automatic speech translation models on 20 African languages
Sahara-TTS
The first production pan-African accented speech synthesis model with 54 personas from 13 countries, representing 34 African accents with female and male voices.
Sahara Voice Lock
Spoof-aware Voice authentication and security, tuned for African voices, accents and languages to combat fraud and deepfakes
Cloud Partners
Use Cases
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Medical Dictations
SOTA automatic speech translation models on 20 African languages
Punching way above models 2-3x its size, Sahara demonstrates superior performance on Accented English speech in a pan-African context across multiple industries (health, finance, legal, academia, etc) and domains with impressive robustness to background noise, intonations, and domain-specific vocabulary.
🇺🇸 Markus White
Legal & Parliamentary
Let’s Get in Touch
Spoof-aware Voice authentication and security, tuned for African voices, accents and languages to combat fraud and deepfakes