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VOX

Nepali speech-to-text platform

Converts spoken Nepali into written text for professional and official use, with speaker separation and noise reduction. Trained on custom Nepali speech corpora spanning regions, age groups and everyday contexts.

Category
Speech recognition
Platform
Web
Accuracy
95% transcription accuracy, 15% character error rate
Models
Wav2Vec 2.0 (acoustic)Pyannote (diarization)
Trained with
PyTorch
VOX speech-to-text: a speaking mouth and a live sound waveform on a screen, with the spoken Nepali appearing as typed text beside it

What the product does

Capabilities

High transcription accuracy

95% accuracy on Nepali speech-to-text conversion, giving precise and reliable transcription for clear speech.

Multi-speaker recognition

Speaker diarization distinguishes between voices, which is what makes VOX usable for meetings and discussions rather than monologues.

Localized for Nepali

Tailored to the Nepali language and its dialects, so native speakers get transcription accuracy and usability that generic tools do not offer.

Optimized for professional use

A 15% character error rate together with noise reduction keeps performance reliable in government and professional settings.

Continuous learning

Adaptive learning and ongoing model refinement mean accuracy and reliability keep improving after deployment.

Built for real rooms

Noise reduction algorithms are part of the pipeline, not an afterthought, for recordings made in imperfect conditions.

How it is put together

Architecture

Acoustic model
Wav2Vec 2.0, fine-tuned to minimise transcription error on Nepali speech.
Speaker separation
Pyannote diarization to tell voices apart across a recording.
Context handling
Acoustic models tuned to capture the contextual nuances a literal transcript would lose.
Noise
Built-in reduction algorithms for performance in challenging environments.
Training stack
PyTorch, with continuous adaptation and model refinement.

Who it is for

Where it is used

Government and public record

Accurate documentation of proceedings and public sessions, which is what makes transparent record-keeping practical at scale.

Education and research

Lectures, seminars and interviews digitized and archived instead of lost to a recording nobody has time to type up.

Business operations

Meetings, customer support and media transcription at volume, in the language the room is actually speaking.