Whisper-medium-fleurs-lang-id Open-source Speech Language Identification Model - Free Deployment, with an Accuracy of up to 88.05%

Whisper Medium Fleurs Lang Id

Developed by sanchit-gandhi

A speech language identification model fine-tuned on OpenAI Whisper-medium, achieving 88.05% accuracy on the FLEURS dataset

Downloads 590.30k

Release Time : 2/23/2023

Model Overview

This model is specifically designed for speech language identification tasks, capable of accurately identifying the language category of audio clips

High Accuracy Language Identification

Achieves 88.05% identification accuracy on the FLEURS evaluation set

Based on Whisper Architecture

Fine-tuned from OpenAI's powerful Whisper-medium model, inheriting its excellent speech processing capabilities

Multi-GPU Training Optimization

Utilizes multi-GPU distributed training with gradient accumulation techniques to improve training efficiency

Speech Language Identification

Audio Classification

Speech Processing

Multilingual Speech Classification

Automatically identifies the language category of audio clips

88.05% identification accuracy

Speech Content Preprocessing

Pre-identifies language types for speech recognition systems

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0152	1.0	8494	0.9087	0.8431
0.0003	2.0	16988	1.0059	0.8460
0.0	3.0	25482	0.8413	0.8805

Property	Details
Model Type	Fine - tuned version of openai/whisper - medium for audio classification
Training Data	FLEURS subset of the google/xtreme_s dataset
License	Apache - 2.0

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