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Accent Id Commonaccent Ecapa

Developed by Jzuluaga
This model uses the ECAPA-TDNN architecture to classify 16 accents in English speech and is trained on the CommonAccent dataset, achieving a test accuracy of 87%.
Downloads 2,291
Release Time : 1/8/2023

Model Overview

This is a speech accent recognition model that can identify 16 different accents from English speech recordings. The model is based on the ECAPA-TDNN architecture and is trained on the CommonAccent dataset, which can be used to improve the processing ability of automatic speech recognition systems for accented speech.

Model Features

High accuracy
Achieves an accuracy of 87% on the test set, outperforming the baseline model
Multi-accent support
Supports the recognition of 16 different English accents
Data augmentation
Uses data augmentation techniques to improve the model's generalization ability
Transfer learning
Fine-tuned based on the VoxCeleb pre-trained model

Model Capabilities

Speech classification
Accent recognition
English speech processing

Use Cases

Speech recognition enhancement
Improve the recognition rate of ASR systems for accented speech
Optimize the speech recognition parameters of ASR systems by identifying the speaker's accent
Can significantly improve the understanding ability of automatic speech recognition systems for accented speech
Speech analysis
Speaker accent analysis
Analyze the accent features in speech samples
Can be used for linguistic research or user profile analysis
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