Whisper AI
Whisper is an open-source automatic speech recognition system from OpenAI that approaches human-level accuracy and robustness for transcribing and translating speech in multiple languages.
https://openai.com/index/whisper/
Product Information
Updated:Nov 12, 2024
Whisper AI Monthly Traffic Trends
Whisper AI received 526.0m visits last month, demonstrating a Slight Decline of -4.6%. Based on our analysis, this trend aligns with typical market dynamics in the AI tools sector.
View history trafficWhat is Whisper AI
Whisper is an artificial intelligence model developed by OpenAI for automatic speech recognition (ASR). Released in September 2022, Whisper was trained on 680,000 hours of multilingual and multitask supervised data collected from the web. It can transcribe speech in multiple languages, translate speech to English, and identify the language being spoken. OpenAI has open-sourced both the model and inference code to enable further research and development of speech processing applications.
Key Features of Whisper AI
Whisper AI is an advanced automatic speech recognition (ASR) system developed by OpenAI. It is trained on 680,000 hours of multilingual and multitask supervised data, resulting in improved robustness to accents, background noise, and technical language. Whisper can transcribe speech in multiple languages, translate to English, and perform tasks like language identification and phrase-level timestamps. It uses a simple end-to-end Transformer-based encoder-decoder architecture and is open-sourced for further research and application development.
Multilingual Capability: Supports transcription and translation across multiple languages, with about one-third of its training data being non-English.
Robust Performance: Demonstrates improved robustness to accents, background noise, and technical language compared to specialized models.
Multitask Functionality: Capable of performing various tasks including speech recognition, translation, language identification, and timestamp generation.
Large-scale Training: Trained on 680,000 hours of diverse audio data, leading to enhanced generalization and performance across different datasets.
Open-source Availability: Models and inference code are open-sourced, allowing for further research and development of applications.
Use Cases of Whisper AI
Transcription Services: Accurate transcription of audio content for meetings, interviews, and lectures across multiple languages.
Multilingual Content Creation: Assisting in the creation of subtitles and translations for videos and podcasts in various languages.
Voice Assistants: Enhancing voice-controlled applications with improved speech recognition and language understanding capabilities.
Accessibility Tools: Developing tools to assist individuals with hearing impairments by providing real-time speech-to-text conversion.
Language Learning Platforms: Supporting language learning applications with accurate speech recognition and translation features.
Pros
High accuracy and robustness across diverse audio conditions and languages
Versatility in performing multiple speech-related tasks
Open-source availability promoting further research and development
Zero-shot performance capability on various datasets
Cons
May not outperform specialized models on specific benchmarks like LibriSpeech
Requires significant computational resources due to its large-scale architecture
Potential privacy concerns when processing sensitive audio data
How to Use Whisper AI
Install Whisper: Install Whisper using pip by running: pip install git+https://github.com/openai/whisper.git
Install ffmpeg: Install the ffmpeg command-line tool, which is required by Whisper. On most systems, you can install it using your package manager.
Import Whisper: In your Python script, import the Whisper library: import whisper
Load the Whisper model: Load a Whisper model, e.g.: model = whisper.load_model('base')
Transcribe audio: Use the model to transcribe an audio file: result = model.transcribe('audio.mp3')
Access the transcription: The transcription is available in the 'text' key of the result: transcription = result['text']
Optional: Specify language: You can optionally specify the audio language, e.g.: result = model.transcribe('audio.mp3', language='Italian')
Whisper AI FAQs
Whisper is an automatic speech recognition (ASR) system developed by OpenAI. It is trained on 680,000 hours of multilingual and multitask supervised data collected from the web, and can transcribe speech in multiple languages as well as translate it to English.
Related Articles
Popular Articles
Best AI Tools for Work in 2024: Elevating Presentations, Recruitment, Resumes, Meetings, Coding, App Development, and Web Build
Dec 12, 2024
Google Gemini 2.0 Update builds on Gemini Flash 2.0
Dec 12, 2024
ChatGPT Is Currently Unavailable: What Happened and What's Next?
Dec 12, 2024
Top 8 AI Meeting Tools That Can Boost Your Productivity | December 2024
Dec 12, 2024
Analytics of Whisper AI Website
Whisper AI Traffic & Rankings
526M
Monthly Visits
#94
Global Rank
#6
Category Rank
Traffic Trends: May 2024-Oct 2024
Whisper AI User Insights
00:01:38
Avg. Visit Duration
2.18
Pages Per Visit
57.1%
User Bounce Rate
Top Regions of Whisper AI
US: 18.97%
IN: 8.68%
BR: 5.9%
CA: 3.52%
GB: 3.47%
Others: 59.46%
Latest AI Tools Similar to Whisper AI
Ticknotes
Ticknotes is an AI-powered meeting assistant that automatically records, transcribes, and generates personalized meeting summaries, action items, and key insights from audio, video, and text content.
Feta
Feta is an AI-powered meeting tool that helps product and engineering teams run efficient meetings by capturing discussions, automating tasks, and providing actionable insights through smart summaries and integrations.
TranscriptionPlus
TranscriptionPlus is an AI-powered transcription service that offers accurate speech-to-text conversion with advanced features like speaker identification, summary generation, and multi-language support at affordable pricing tiers.
AudioScribe.io
AudioScribe.io is a revolutionary AI-powered transcription service that converts audio and video content into accurate text while offering advanced features like automated meeting recording, full-text search, and multi-language support.
Popular AI Tools Like Whisper AI
TurboScribe
TurboScribe is an AI-powered transcription service that converts audio and video files to accurate text in seconds, supporting 98+ languages with 99.8% accuracy and unlimited transcriptions.
Happy Scribe
Happy Scribe is an all-in-one audio transcription and video subtitling platform that uses AI and human professionals to convert speech to text in 120+ languages with up to 99% accuracy.
Sonix AI
Sonix AI is an automated transcription, translation, and subtitling platform that uses cutting-edge artificial intelligence to quickly and accurately convert audio and video files to text in over 40 languages.
AssemblyAI
AssemblyAI is an AI company offering industry-leading speech recognition and natural language processing APIs for transcribing and analyzing audio data at scale.