https://github.com/Trint-ai/TrintAI I've been working on integrating different opensource tools and ML models to create TrintAI. TrintAi is a powerful open-source tool for transcribe and understand speech with multiple capabilities.
This is an open-source alternative to paid services like:
AssemblyAI
Deepgram
Gladia
Google Cloud
Microsoft Azure
RevAI
With trintAI you can build your own custom workflows & integration for speech-to-text transcription.
The main features are:
- Speech-to-Text Transcription: Converts audio files into accurate, readable text in real-time.
- Summarization: Provides concise summaries of long audio files or transcripts. This feature extracts the most important information and key points from the text, allowing you to quickly understand the main takeaways from meetings, calls, or any extended audio content.
- Sentiment Analysis: Detects emotions within the transcribed text.
- Language Identification: Detects the language spoken in the audio file and can transcribe in multiple languages.
- Diarization: Identify and distinguish between different speakers within an audio recording.
Give it a try! it is open-source. Your feedback is very appreciated!
This is an open-source alternative to paid services like:
AssemblyAI Deepgram Gladia Google Cloud Microsoft Azure RevAI
With trintAI you can build your own custom workflows & integration for speech-to-text transcription.
The main features are:
- Speech-to-Text Transcription: Converts audio files into accurate, readable text in real-time.
- Summarization: Provides concise summaries of long audio files or transcripts. This feature extracts the most important information and key points from the text, allowing you to quickly understand the main takeaways from meetings, calls, or any extended audio content.
- Sentiment Analysis: Detects emotions within the transcribed text.
- Language Identification: Detects the language spoken in the audio file and can transcribe in multiple languages.
- Diarization: Identify and distinguish between different speakers within an audio recording.
Give it a try! it is open-source. Your feedback is very appreciated!
Cheers