Whisper (OpenAI)
Pricing model
Upvote
0
Whisper is a publicly available system for automatic speech recognition, developed using 680,000 hours of multilingual and multi-task supervised data sourced from the internet. It is crafted to effectively handle various accents, background noise, and technical jargon, and it can convert and translate spoken language in numerous tongues into English. This straightforward end-to-end method is executed as an encoder-decoder Transformer. Additionally, it can identify languages and provide timestamps at the phrase level. It aims to offer ease of use and high precision, enabling developers to integrate voice interfaces into more applications.
Similar neural networks:
Upvote
0
Rythmex is a contemporary tool for converting audio to text, capable of transcribing various audio and video file formats online. It provides 30 minutes of free audio transcription and supports multiple text formats. This service is ideal for numerous applications in business, education, and professional settings, making it beneficial for radio stations, transcription services, newsrooms, podcasts, interviews, filmmakers, video producers, lawyers, journalists, students, and marketers.
Upvote
0
TacoTranslate is a localization tool designed to simplify the process of expanding React applications into different markets. It automatically gathers and translates all text strings found in the React application code, removing the necessity of manually handling JSON files. Equipped with AI, it guarantees contextually precise translations that are customized to match the product’s tone. Additionally, users have the option to enhance any of the translations manually through TacoTranslate's intuitive interface.
Upvote
0
Whisper is a publicly available system for automatic speech recognition, developed using 680,000 hours of multilingual and multi-task supervised data sourced from the internet. It is crafted to effectively handle various accents, background noise, and technical jargon, and it can convert and translate spoken language in numerous tongues into English. This straightforward end-to-end method is executed as an encoder-decoder Transformer. Additionally, it can identify languages and provide timestamps at the phrase level. It aims to offer ease of use and high precision, enabling developers to integrate voice interfaces into more applications.