Common7 Open-source Automatic Speech Recognition Model - Free Deployment to Facilitate Precise Persian Speech-to-Text Conversion

Common7

Developed by ghofrani

This model is an automatic speech recognition (ASR) model fine-tuned on the Mozilla Common Voice 7.0 Persian dataset, specifically designed for Persian speech-to-text tasks.

Speech Recognition

Transformers

Other#Persian speech recognition #Common Voice dataset #Low word error rate

Downloads 23

Release Time : 3/2/2022

Model Overview

A speech recognition model optimized for Persian, capable of converting Persian speech into text, suitable for applications such as voice assistants and subtitle generation.

Model Features

Persian Optimization

Specifically trained and optimized for Persian speech characteristics

Based on Common Voice Dataset

Trained using Mozilla's high-quality open-source speech dataset

Gradual Performance Improvement

Word error rate (WER) gradually decreased from 1.0 to 0.3478 during training

Model Capabilities

Persian speech recognition

Speech-to-text

Continuous speech recognition

Use Cases

Speech Transcription

Persian Speech Transcription

Convert Persian speech content into text format

Word error rate 0.3478

Assistive Technology

Voice-Controlled Applications

Provide voice control interfaces for Persian-speaking users

🚀 common7

This model is a fine - tuned version of common7/checkpoint - 18500 on the MOZILLA - FOUNDATION/COMMON_VOICE_7_0 - FA dataset. It offers a solution for automatic speech recognition, leveraging the pre - trained model and fine - tuning on the specific dataset.

🚀 Quick Start

This model is a fine - tuned version of common7/checkpoint-18500 on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - FA dataset. It achieves the following results on the evaluation set:

Loss: 0.3448
Wer: 0.3478

📚 Documentation

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 6e - 05
train_batch_size: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 150.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.957	3.29	500	2.9503	1.0
1.7225	6.58	1000	0.8860	0.7703
1.4907	9.86	1500	0.6555	0.6673
1.4177	13.16	2000	0.5784	0.6076
1.3425	16.45	2500	0.5379	0.5718
1.33	19.73	3000	0.4962	0.5245
1.4378	23.03	3500	0.4699	0.5098
1.1894	26.31	4000	0.4527	0.4848
1.1844	29.6	4500	0.4309	0.4651
1.1795	32.89	5000	0.4131	0.4524
1.1471	36.18	5500	0.4052	0.4435
1.1337	39.47	6000	0.3927	0.4363
1.1896	42.76	6500	0.3811	0.4254
1.1847	46.05	7000	0.3855	0.4129
0.9954	49.34	7500	0.3729	0.3981
1.0293	52.63	8000	0.3637	0.4014
1.0224	55.92	8500	0.3578	0.3885
1.012	59.21	9000	0.3629	0.3930
1.0772	62.5	9500	0.3635	0.3906
1.0344	65.79	10000	0.3469	0.3771
0.9457	69.08	10500	0.3435	0.3735
0.9307	72.37	11000	0.3519	0.3762
0.9523	75.65	11500	0.3443	0.3666
0.9523	78.94	12000	0.3502	0.3757
0.9475	82.24	12500	0.3509	0.3643
0.9971	85.52	13000	0.3502	0.3626
0.9058	88.81	13500	0.3472	0.3605
0.8922	92.1	14000	0.3530	0.3618
0.9	95.39	14500	0.3500	0.3574
0.9051	98.68	15000	0.3456	0.3535
0.9304	101.97	15500	0.3438	0.3578
0.9433	105.26	16000	0.3396	0.3530
0.8988	108.55	16500	0.3436	0.3539
0.8789	111.84	17000	0.3426	0.3516
0.8667	115.13	17500	0.3438	0.3506
0.8895	118.42	18000	0.3434	0.3503
0.8888	121.71	18500	0.3425	0.3494
0.9453	125.0	19000	0.3415	0.3480
0.9267	128.29	19500	0.3477	0.3503
0.8315	131.58	20000	0.3476	0.3505
0.8542	134.86	20500	0.3475	0.3506
0.8478	138.16	21000	0.3430	0.3481
0.8643	141.45	21500	0.3451	0.3485
0.8705	144.73	22000	0.3444	0.3474
0.9869	148.03	22500	0.3441	0.3493

Framework versions

Transformers 4.17.0.dev0
Pytorch 1.10.2
Datasets 1.18.3.dev0
Tokenizers 0.10.3

Property	Details
Language	Persian (fa)
Tags	automatic - speech - recognition, mozilla - foundation/common_voice_7_0, generated_from_trainer
Datasets	common_voice
Model Name	common7

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