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Wav2vec2 Base Common Voice Persian Colab

Developed by zoha
This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base for Persian language datasets, primarily used for Persian speech-to-text tasks.
Downloads 21
Release Time : 5/26/2022

Model Overview

This is an automatic speech recognition (ASR) model optimized for Persian, based on the wav2vec2 architecture and fine-tuned on the Common Voice Persian dataset, suitable for Persian speech transcription scenarios.

Model Features

Persian Optimization
Specially fine-tuned for Persian speech characteristics to improve recognition accuracy
Based on wav2vec2
Utilizes Facebook's open-source wav2vec2-base architecture with powerful speech feature extraction capabilities
Colab Compatible
The model name indicates its suitability for use in Google Colab environments

Model Capabilities

Persian speech recognition
Speech-to-text
Audio content transcription

Use Cases

Speech Transcription
Persian Speech Transcription
Convert Persian speech content into text format
Word Error Rate (WER) 0.6911
Voice Assistants
Persian Voice Command Recognition
Used for voice command recognition in Persian voice assistants or control systems
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