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Wav2vec2 Base Toy Train Data Random Low Pass
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Wav2vec2 Base Toy Train Data Random Low Pass

Developed by scasutt
This model is a speech recognition model fine-tuned on an unknown dataset based on facebook/wav2vec2-base, primarily used for Automatic Speech Recognition (ASR) tasks.
Speech Recognition
Transformers
Open Source License:Apache-2.0#Speech recognition fine-tuning#Low-pass filtered data#WER optimization
Downloads 29
Release Time : 3/31/2022

Model Overview

This is a speech recognition model based on the wav2vec2 architecture, fine-tuned for converting speech to text. The model achieved a word error rate of 0.7288 on the evaluation set.

Model Features

Based on wav2vec2 architecture
Uses Facebook's wav2vec2-base as the foundational architecture, offering excellent speech recognition capabilities
Fine-tuning optimization
Fine-tuned on a specific dataset, potentially optimizing recognition performance for particular domains or scenarios
Low-pass filtering
The model name includes 'low_pass', suggesting possible low-pass filtering of audio inputs

Model Capabilities

Speech recognition
Audio-to-text conversion

Use Cases

Speech transcription
Meeting minutes
Automatically convert meeting recordings into text transcripts
Voice notes
Convert voice memos into searchable text
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