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Wav2vec2 Base Common Voice 50p Persian Colab

Developed by zoha
This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base for Persian language, supporting Persian speech-to-text tasks.
Downloads 21
Release Time : 6/2/2022

Model Overview

This is an optimized Automatic Speech Recognition (ASR) model for Persian, based on the wav2vec2 architecture and fine-tuned on the Common Voice Persian dataset.

Model Features

Persian Optimization
Specifically fine-tuned for Persian speech recognition tasks
Based on wav2vec2
Uses Facebook's wav2vec2-base architecture as the base model
Moderate Performance
Achieves a 65.37% Word Error Rate (WER) on the evaluation set

Model Capabilities

Persian speech recognition
Speech-to-text

Use Cases

Speech Transcription
Persian Speech Transcription
Convert Persian speech content into text
Word Error Rate around 65.37%
Voice Assistants
Persian Voice Command Recognition
Basic speech recognition component for Persian voice assistants
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