whisper-small-fa-lora

Whisper-Small Persian STT — LoRA Fine-Tuned

A fine-tuned version of openai/whisper-small for Persian speech-to-text (ASR) using LoRA.
This model is optimized for persian conversational speech and dataset-quality audio.

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Model Details

Model Description

This model is a LoRA fine-tuned Whisper Small focused on Persian (fa) speech recognition.
It improves transcription accuracy on standard Persian audio segments (16kHz, mono, normalized WAV).

• Developed by: Mehdi Pouladrag
• Model type: Speech-to-Text (ASR) — Whisper Small (Seq2Seq Transformer)
• Language(s): Persian (fa)
• License: MIT (or your preferred license)
• Finetuned from: openai/whisper-small
• Dataset: persian-voice-v1 (single dataset)
• Training technique: LoRA (Low-Rank Adaptation)

Model Sources

• Repository: https://github.com/Mehdipoladrag/Fine-tuning-Whisper-Model

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Uses

Direct Use

• Convert Persian speech to text
• Subtitle generation for Persian audio
• Conversational ASR
• Podcast / video transcription
• General Persian content recognition

Downstream Use

• Integrate into ASR pipelines
• Use in real-time Persian voice applications
• Further fine-tuning on custom Persian domains (medical, legal, etc.)

Out-of-Scope Use

• Non-Persian audio
• Low-quality/noisy multi-speaker overlapping speech
• Misuse for surveillance or unethical monitoring

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Bias, Risks, and Limitations

• Whisper may still struggle with dialect-heavy, noisy, or low-quality audio.
• The dataset used is relatively limited (~6099 audio–subtitle pairs), so:
  • Certain accents may be underrepresented.
  • Model may hallucinate or mis-transcribe in rare cases.

Recommendations

Users should:

• Provide clean 16kHz mono WAV audio
• Use domain-specific fine-tuning if necessary
• Validate outputs before critical use