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Nivision
Hebrew Speech-to-Text

A Speech-to-Text engine trained specifically on Hebrew.

Nivision uses a speech-to-text engine trained on Hebrew speech - not generic Whisper and not a translation from English. High accuracy on clean calls and resilience to challenging audio.

What is Hebrew Speech-to-Text

The technology that turns Hebrew audio into clean text - the foundation of every call analysis.

Speech-to-Text (STT) is the underlying technology that turns an audio file into text. Hebrew STT is significantly harder than English STT because Hebrew is a dense language with rich morphology, and call-center audio mixes in Israeli slang, English words, and occasionally Arabic or Russian. A high-quality Hebrew STT engine has to be trained on natural Hebrew speech - not rely on translation from an English model.

How it works

Four factors that produce operational-grade Hebrew STT:

Quality Hebrew STT is more than a single model. It requires a combination of acoustics, linguistics, call environment and real operational requirements.

01

Acoustic + language model trained on Hebrew

The engine combines an acoustic model (how Hebrew sounds) and a language model (how Hebrew grammar works). Both are trained on large volumes of natural Hebrew speech.

02

Coverage across accents and speakers

Native, immigrant, and second-language Hebrew speakers - the model is trained on a wide range to handle the actual speaker population of Israeli call centers.

03

Robustness to noise and compressed audio

Phone-call audio is heavily compressed compared to studio recordings. The engine is preprocessed and trained on real call audio to handle quality gaps.

04

Fast post-call transcription at scale

Nivision processes transcription post-call: every call is available within minutes of ending. Batch processing handles large volumes of historic recordings at the same quality. In-call real-time streaming is on the roadmap.

Who it's for

Who needs a Hebrew-specific Speech-to-Text engine?

Quality Hebrew STT is infrastructure. It matters anywhere Hebrew audio needs to be turned into text you can act on - not just record.

  • Call centers transcribing calls for analysis or QA
  • Insurance and finance organizations bound to compliance recording
  • Product teams analyzing customer calls to surface issues
  • AI teams that need an accurate STT layer in their language and domain
  • Internal systems that need automatic transcription of Hebrew calls
Comparison

Three categories of Hebrew STT engines - which fits call centers?

Anyone searching for Hebrew STT runs into three categories of tools, and the fit depends on required accuracy, volume, and the operational environment.

The comparison below is at the category level, not the level of specific products.

STT engine categoryAccuracy on Hebrew call audioSpeaker separationTelephony audio handlingOperational integrationLocal supportRecommended fit
Generic open-source models (Whisper-class)Moderate, version-dependentNot built-inLimitedRequires custom buildCommunityR&D projects and self-built pipelines
International cloud STT servicesGood on clean audio, drops on call audioAdd-onLimitedAPI onlyGeneric, not localProjects that need a generic speech recognition API
Hebrew call-center STT (like Nivision)High, built for call audioBuilt-inYesFull platformIsraeli, call-center focusedCall centers that need a full operational solution
What you actually get

The outcome

  • Accurate transcripts for both human reading and downstream AI
  • Automatic speaker separation with no configuration
  • Transcripts available within minutes of call end - powering alerts and a continually-refreshed dashboard
  • Batch transcription of historic recording archives
  • STT infrastructure you do not have to maintain yourself
  • An engine that improves over time on your conversation domain
Hebrew Speech-to-Text

FAQ

How is a Hebrew-specific STT engine better than a generic model like Whisper?

Generic models are trained primarily on English and then add Hebrew as a secondary language. An engine trained specifically on Hebrew goes deeper - an acoustic model that knows the sounds of spoken Hebrew, a language model that understands Hebrew grammar, and call-center audio handling in particular. The result: higher accuracy on real calls, especially those with Israeli slang.

What is your accuracy on telephony audio (low sample rate)?

Phone-call audio is typically 8kHz, significantly lower than studio recordings. Our engine is trained specifically on telephony audio, so accuracy remains high even at low sample rates - unlike models trained only on high-quality audio.

Does the system provide word-level timestamps?

Yes. Every transcript comes with word-level timestamps - useful for precise search inside a call, syncing playback to specific points, and analyzing speaking pace for both agent and customer.

Is your STT available as a standalone API?

Nivision is sold as a full platform - transcription is one component of it. If you need only an STT layer, please reach out and describe the scenario so we can suggest the right fit.

How fast is a transcript available after a call ends?

Nivision processes transcription post-call: the transcript is available within minutes of the call ending. In-call real-time streaming (sub-second latency) is on the roadmap; for most call-center use cases, the post-call transcript is fast enough to power alerts, the dashboard, summaries and CRM sync.

What about overlapping voices or calls with more than two speakers?

The system supports speaker separation in calls with 3-4 participants (for example: a sales call with two reps and one customer). Separation accuracy drops slightly with very similar voices or heavy overlap, but remains usable for analysis.

Does the model learn the unique terminology of my company?

Yes. You can load a custom term dictionary (product names, acronyms, professional terms) that improves accuracy on expressions uncommon in general Hebrew. The system also gradually learns from your calls.

What about the security of the audio and transcripts?

All audio and transcripts are encrypted at rest and in transit, and retention policies are configurable. Nivision supports the security and compliance standards required by Israeli regulated industries. Full details: /security.

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