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Transform audio/video to text with precision, supporting 1500+

GPT-4o-transcribe is an OpenAI model for speech-to-text conversion, developed as an upgrade to the Whisper model, with a focus on improving transcription accuracy and reducing the word error rate. It supports over 100 languages and works in environments involving noise, different accents, and varying speech rates; it also incorporates techniques for noise reduction and semantic speech activity detection. The model supports real-time speech-to-text conversion, allowing for continuous audio input and real-time text output. It can be used in call centers, for creating meeting minutes, in smart assistants, and in applications that require voice interaction.

Transcribe, diarize, and translate live global conversations.

Buzz is an open-source tool for converting audio to text and translating audio locally on the user's device; it is based on Whisper models. It allows users to convert audio and video files and YouTube links to text, as well as transcribe audio directly from the microphone.

TurboScribe uses artificial intelligence to transcribe audio files and videos into text, leveraging Whisper technology. It supports more than 98 languages, with an accuracy rate of up to 99.8%, according to the platform.

Convert audio to text with AI-powered transcription.

Transcribe audio files into text with AI, all on your device.

Transcribe WhatsApp audio to text effortlessly

Amical is a voice dictation and speech-to-text tool that allows users to speak instead of typing, with the option to run AI models locally on the device or use cloud-based models.

Transcribe video to text online free

Audio files transcribed to text

Deepgram is an artificial intelligence platform specializing in voice technologies, presented as the primary engine of the Voice AI economy. It provides companies and developers with high-precision software interfaces for speech-to-text conversion, text-to-speech conversion, and building intelligent voice agents that operate in real time or through batch processing. The platform relies on advanced models that are highly accurate, fast, and realistic, with lower operating costs compared to traditional solutions, and supports multiple deployment models including cloud and self-hosted to meet the requirements of different organizations.