Aljawab (الجواب) builds production-grade Arabic speech recognition, text-to-speech and call-center monitoring. Trained on real 4 kHz and 8 kHz telephony audio across 23+ Arabic dialects — not borrowed from English systems retrofitted to Arabic.
Dialect-aware automatic speech recognition tuned for narrow-band 4/8 kHz call-center audio. Word-level timestamps, speaker diarization, code-switching between Arabic and English, and robustness to the noise, codecs and dynamic range you actually hear in real calls.
Gulf, Levantine, Egyptian, Maghrebi, MSA and the sub-dialects within each — modelled directly, not as an afterthought.
Every recognised word carries a start/end time, enabling alignment, search, redaction and analytics workflows.
Discrete Fourier Transform–based speaker separation cleanly attributes turns to agent vs. caller, even on a single mono channel.
Turn dormant call-center recordings into a fully searchable, indexed archive. Transcripts, speaker turns, word-level timestamps, voiceprint search across calls, and audio-domain PII masking applied to the underlying audio — not just the transcript.
Real-time Arabic monitoring for live agents. Live transcription on 4/8 kHz telephony audio, dialect-aware recognition, diarization, and quality scoring that surfaces issues while the call is still happening.
Four pieces of voice infrastructure underpinning every product Aljawab ships:
On-prem or VPC deployment, audit-ready logs, role-based access, and SLAs sized for the volume of a national contact center. Built to be the Arabic voice layer regulated industries can actually buy.
Yes — the models are trained on real 4 kHz and 8 kHz call-center audio, not upsampled studio data.
23+ dialects across Gulf, Levantine, Egyptian and Maghrebi families, plus MSA.
Yes. Audio-domain PII masking redacts the underlying waveform, not just the transcript.