C

Cat Dog Sounds Classification

Developed by dima806
A foundational speech recognition model based on the wav2vec 2.0 architecture, pre-trained on 960 hours of English speech data
Downloads 25
Release Time : 8/26/2023

Model Overview

This model is an automatic speech recognition (ASR) model capable of converting English speech into text. Based on the Transformer architecture, it is suitable for general speech recognition tasks.

Model Features

End-to-End Speech Recognition
Learns directly from raw audio waveforms without the need for manually designed feature extraction
Self-Supervised Pre-Training
Utilizes large amounts of unlabeled speech data for pre-training to enhance model generalization
Efficient Transformer Architecture
Employs an improved Transformer structure optimized for speech sequence processing efficiency

Model Capabilities

English Speech Recognition
Speech-to-Text
Continuous Speech Recognition

Use Cases

Speech Transcription
Automated Meeting Minutes
Automatically converts meeting recordings into text transcripts
Subtitle Generation
Automatically generates English subtitles for video content
Voice Assistants
Voice Command Recognition
Used for voice control of smart home devices
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