W

Whisperfile

Developed by cjpais
Whisper is a Transformer-based encoder-decoder model for speech recognition and translation tasks, supporting multilingual processing.
Downloads 353
Release Time : 5/17/2024

Model Overview

Whisper is a powerful automatic speech recognition (ASR) system capable of handling speech transcription and translation tasks in multiple languages. It is trained on 1 million hours of weakly labeled audio and 4 million hours of pseudo-labeled audio, with excellent robustness and accuracy.

Model Features

Multilingual support
Supports speech recognition and translation in multiple languages, including newly added support for Cantonese
High robustness
Has stronger robustness against accents, background noise, and professional languages
Efficient chunking processing
Uses a chunking algorithm to process long audio, 9 times faster than traditional sequential algorithms
Timestamp support
Can obtain sentence-level and word-level timestamp information

Model Capabilities

Speech recognition
Speech translation
Multilingual processing
Long audio processing
Timestamp generation

Use Cases

Speech transcription
Meeting minutes
Automatically transcribe meeting recordings into text
High-accuracy text transcription
Podcast transcription
Transcribe podcast content into searchable text
Supports multiple languages and accents
Speech translation
Real-time translation
Translate the speech in one language into text in another language in real-time
Translation accuracy close to the current state-of-the-art
Assistive tools
Accessible applications
Provide speech-to-text services for the hearing-impaired
Improve information accessibility
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
Š 2025AIbase