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Wavlm Base Libri Clean 100
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Wavlm Base Libri Clean 100
Developed by anjulRajendraSharma
Automatic speech recognition model based on the WavLM architecture, fine-tuned on the LibriSpeech CLEAN dataset (100 hours)
Downloads 73
Release Time : 3/2/2022
Model Overview
This model is a fine-tuned version of Microsoft's WavLM-base model, specifically designed for English speech recognition tasks, and performs excellently on the LibriSpeech CLEAN dataset
Model Features
High-precision Speech Recognition
Achieves a word error rate of 7.73% on the LibriSpeech CLEAN test set
Based on WavLM Architecture
Utilizes Microsoft's advanced WavLM self-supervised learning architecture with powerful speech feature extraction capabilities
Lightweight Fine-tuning
Fine-tuned with only 100 hours of clean speech data, preserving the generalization capability of the base model
Model Capabilities
English Speech Recognition
Audio to Text
Speech Content Understanding
Use Cases
Speech Transcription
Automatic Meeting Minutes Transcription
Automatically convert meeting recordings into text transcripts
Approximately 92.27% accuracy (based on 7.73% WER)
Podcast Content Indexing
Create searchable text indexes for podcast audio
Assistive Technology
Hearing Impairment Assistance
Real-time conversion of speech to text display
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