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Wav2vec2 Base Toy Train Data Random High Pass
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Wav2vec2 Base Toy Train Data Random High Pass

Developed by scasutt
A speech recognition model fine-tuned on an empty dataset based on facebook/wav2vec2-base, using random high-pass filter technology to process training data
Speech Recognition
Transformers
Open Source License:Apache-2.0#Speech Recognition#High-pass Filter Enhancement#Low-resource Fine-tuning
Downloads 29
Release Time : 3/30/2022

Model Overview

This is an experimental speech recognition model primarily for demonstration and testing purposes. The model is based on the wav2vec2 architecture, fine-tuned on an empty dataset, and employs random high-pass filter technology for data processing.

Model Features

Random High-pass Filter Processing
Training data undergoes random high-pass filter processing, potentially enhancing the model's ability to recognize high-frequency speech features.
Based on wav2vec2 Architecture
Utilizes Facebook's wav2vec2-base architecture, featuring robust speech feature extraction capabilities.
Experimental Nature
This is an experimental model primarily intended for technical demonstrations and testing purposes.

Model Capabilities

Speech Recognition
Audio Feature Extraction

Use Cases

Speech Technology Research
High-pass Filter Effect Testing
Used to study the impact of high-pass filter processing on speech recognition model performance.
Model Fine-tuning Experiment
Serves as a teaching example for model fine-tuning techniques.
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