Wav2vec2-2-BERT Large Open-Source Model - Free and Precise English Speech-to-Text Conversion

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Wav2vec2 2 Bert Large

Developed by speech-seq2seq

Automatic Speech Recognition (ASR) model trained on LibriSpeech dataset for converting English speech to text

Speech Recognition

Transformers

#Low Word Error Rate #English Speech Recognition #Linear Learning Rate Scheduling

Downloads 17

Release Time : 3/2/2022

Model Overview

This model is an automatic speech recognition system specifically designed for English speech, capable of converting speech signals into corresponding text content.

Model Features

High Accuracy

Achieved a word error rate of 1.9878 on the LibriSpeech evaluation set

Optimized Training

Trained using Adam optimizer with linear learning rate scheduler

Model Capabilities

English Speech Recognition

Continuous Speech-to-Text

Use Cases

Speech Transcription

Audio Transcription

Automatically convert English speech content into text format

Word Error Rate 1.9878

Assistive Tools

Real-time Caption Generation

Provide real-time captions for English videos or meetings

Training Loss	Epoch	Step	Validation Loss	Wer
6.7599	0.28	500	6.8755	1.2551
6.5943	0.56	1000	6.7702	1.5878
6.3146	0.84	1500	6.6981	1.6627
6.6112	1.12	2000	6.6760	1.9853
6.6894	1.4	2500	6.6323	1.9376
6.5525	1.68	3000	6.6185	1.9383
6.571	1.96	3500	6.6126	1.9580
6.3363	2.24	4000	6.7869	1.9818
6.5832	2.52	4500	6.9096	2.0025
6.3523	2.8	5000	6.9670	1.9878

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Wav2vec2 2 Bert Large

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 Speech Recognition Model

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

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