Arabic speech to text that understands Saudi dialects
Transform recorded calls, meetings, and live audio into accurate, structured text. Built for enterprise accuracy in noisy, multilingual environments.
Record or upload to transcribe
MP3, WAV, M4A, MP4 — up to 5MB
20+ languages · 95%+ accuracy
CAPABILITIES
Transcription built for enterprise
Real-time Transcription
Transcribe live audio streams instantly with sub-second latency, perfect for contact centers and live support.
Multi-language Support
Accurately transcribe Arabic, English, French, Spanish, and 20+ other languages with dialect awareness.
Enterprise-grade Accuracy
Over 95% word-error-rate accuracy on business audio, including noisy call center environments.
Post-call Processing
Automatically transcribe recorded calls in bulk — hours of audio processed in minutes.
What Arabic speech to text from Hams.AI does
Speech to text (STT) converts spoken audio into written text. Generic engines are trained mostly on English and on Modern Standard Arabic read from scripts, so they fail on what customers actually do on the phone: speak in Saudi or Gulf dialect, mix in English words, and talk over background noise. Hams.AI STT is trained for that reality, with dialect-aware Arabic recognition and English as a full second language.
It is the same recognition layer that listens inside our AI voice agent and cloud contact center, and its transcripts feed post-call analytics directly.
How it works
From audio to searchable text in four steps.
- 1
Send audio, live or recorded
Stream live audio from a call or a microphone, or upload recorded calls and meetings in bulk through the API.
- 2
Recognise the dialect
The engine handles Arabic dialects and English within the same conversation and transcribes both, without asking the speaker to switch.
- 3
Get structured text
Receive a time-aligned transcript that is ready for search, summaries and quality scoring.
- 4
Act on it
Push transcripts to post-call analytics for summaries, categories and compliance checks, or into your CRM and ticketing systems. Audio and text stay in Saudi data centers.
Supported languages and dialects
Recognition is benchmarked on real call audio, not read speech. The table shows what to expect for each audience.
| Language / variety | Best for | Notes |
|---|---|---|
| Modern Standard Arabic (الفصحى) | Broadcast, formal meetings, government sessions, e-learning | Highest accuracy on scripted or formal speech. |
| Saudi dialects | Customer calls inside the Kingdom, branch and field conversations | Trained on how customers really speak, including fillers and switching into English mid-sentence. |
| Gulf dialects | GCC customer calls and meetings | Regional coverage for brands operating across the Gulf. |
| English | International customers, internal meetings, mixed-language calls | A full second language; mixed Arabic-English sentences are transcribed as spoken. |
Where Arabic STT is used
Call recording analysis and QA
Transcribe every call, not a sample, so quality teams can score all conversations and find the reasons behind complaints.
Meeting transcription
Turn internal meetings and customer sessions into searchable notes and action items, with Arabic and English in the same document.
Compliance and record keeping
Keep a text record of what was said on regulated calls, searchable for audits and disputes, hosted in the Kingdom.
Voice applications and subtitles
Add voice input to apps and generate Arabic subtitles for videos and training content.
Why enterprises in Saudi Arabia choose Hams.AI for transcription
STT is where accuracy on Arabic matters most: a transcript that misses the dialect misses the intent. Hams.AI STT is the listening layer of our AI voice agent and cloud contact center, its output feeds post-call analytics, and all processing happens in Saudi data centers under security and compliance controls aligned with NCA, PDPL, SDAIA and MCIT guidance. It integrates with Genesys, Cisco, SAP, Google Cloud, Microsoft and WhatsApp.
Integration and deployment
Live transcription runs over a streaming connection from your telephony or contact-center platform; batch transcription takes recorded files through the API and returns text with timestamps. The connectors for Genesys, Cisco, SAP, Google Cloud, Microsoft and WhatsApp are the same ones used by the voice agent and cloud contact center, so transcripts land next to the conversation they came from and flow into post-call analytics, CRM and ticketing without a separate pipeline. Most teams start by transcribing recorded calls in bulk to benchmark accuracy on their own dialect mix, then switch on live transcription for the voice agent and agent assist.
Processing runs in Saudi data centers by default. For public-sector and regulated customers, data residency, redaction of sensitive data and audit requirements are agreed in the order form, and the security page lists the controls in place.
Arabic speech to text: frequently asked questions
Have another question? Reach out to our team.
Speech to text, also called automatic speech recognition (ASR) or transcription, converts spoken audio into written text. Arabic is harder than most languages because everyday speech differs from written Modern Standard Arabic and varies by region. Hams.AI STT is trained on dialectal Arabic and English so that customer calls are transcribed as they were spoken.
What is Arabic speech to text?
Which dialects does it understand?
How accurate is it on call center audio?
Does it work in real time?
Where is the audio processed, and is it compliant?
How do I try it, and what does it cost?
Start transcribing audio today
Join thousands of enterprises using Hams AI to turn every conversation into structured, actionable intelligence.