wav2vec2-large-xls-r-300m-maltese Open Source Speech Recognition Model - Free Realization of Maltese Speech-to-Text

Wav2vec2 Large Xls R 300m Maltese

Developed by infinitejoy

This is an automatic speech recognition (ASR) model fine-tuned on Maltese speech datasets based on the facebook/wav2vec2-xls-r-300m model.

Speech Recognition

Transformers

OtherOpen Source License:Apache-2.0 #Maltese speech recognition #Low word error rate #Multilingual support

Downloads 19

Release Time : 3/2/2022

Model Overview

This model is specifically designed for Maltese speech recognition tasks, achieving a word error rate (WER) of 23.5% and a character error rate (CER) of 5.07% on the Common Voice 7 dataset.

Model Features

Dedicated Maltese Speech Recognition

Speech recognition model specifically optimized for Maltese

Based on XLS-R Architecture

Uses facebook's XLS-R-300M large-scale pre-trained model as the foundation

Robust Speech Processing Capability

Capable of handling various speech scenarios and dialogue content

Model Capabilities

Maltese speech-to-text

Automatic speech recognition

Dialogue speech processing

Use Cases

Speech Transcription

Maltese Speech Transcription

Convert Maltese speech content into text

Word error rate 23.5%, character error rate 5.07%

Voice Assistants

Maltese Voice Interaction

Used for developing Maltese voice assistants and dialogue systems

🚀 wav2vec2-large-xls-r-300m-maltese

This model is a fine - tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA - FOUNDATION/COMMON_VOICE_7_0 - MT dataset, which is used for automatic speech recognition and can achieve good results in related tasks.

🚀 Quick Start

This model is a fine - tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA - FOUNDATION/COMMON_VOICE_7_0 - MT dataset. It achieves the following results on the evaluation set:

Loss: 0.2005
Wer: 0.1897

✨ Features

Language: mt
License: apache - 2.0
Tags: automatic - speech - recognition, mozilla - foundation/common_voice_7_0, generated_from_trainer, mt, robust - speech - event, model_for_talk, hf - asr - leaderboard
Datasets: mozilla - foundation/common_voice_7_0

📚 Documentation

Model Index

Name: XLS - R - 300M - Maltese
Results:
- Task:
  - Name: Automatic Speech Recognition
  - Type: automatic - speech - recognition
- Dataset:
  - Name: Common Voice 7
  - Type: mozilla - foundation/common_voice_7_0
  - Args: mt
- Metrics:
  - Name: Test WER
  - Type: wer
  - Value: 23.503
  - Name: Test CER
  - Type: cer
  - Value: 5.065

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

🔧 Technical Details

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 7e - 05
train_batch_size: 32
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2000
num_epochs: 100.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.2238	18.02	2000	0.3911	0.4310
0.7871	36.04	4000	0.2063	0.2309
0.6653	54.05	6000	0.1960	0.2091
0.5861	72.07	8000	0.1986	0.2000
0.5283	90.09	10000	0.1993	0.1909

Framework versions

Transformers 4.16.0.dev0
Pytorch 1.10.1+cu102
Datasets 1.17.1.dev0
Tokenizers 0.11.0

📄 License

This model is released under the apache - 2.0 license.

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