NVIDIA Parakeet TDT High-Quality English Transcription - Install Locally
AI Summary
Summary of Nvidia’s Parakeet Speech-to-Text Model
- Overview: Nvidia has launched the Parakeet model, a new speech-to-text AI that outperforms Whisper 3 large.
- Features:
- Transcribes audio segments of up to 24 minutes in a single pass.
- Contains only 600 million parameters while maintaining high performance.
- Excels in predicting word-level timestamps, punctuation, and specialized audio such as song lyrics.
- Input & Output:
- Accepts 16 kHz monochord wave or FLAC format.
- Outputs well-formatted English text with timing information.
- Architecture: Built for advanced English transcription tasks using an Excel variant of the Fast Conformer.
Installation Steps:
- Set up a Conda environment.
- Clone Nvidia’s Nemo directory and navigate to the ASR examples.
- Install the Nemo toolkit for Automatic Speech Recognition.
- Launch the demo local server on port 7860 using the command provided in the video.
- Upload an audio file to transcribe.
Performance:
- Example transcription with 10-second audio was accurate with timestamps.
- Performance on longer audio (3 minutes) showed exemplary speed and accuracy.
- The model seems optimized for English but handled some French and Spanish subtly.
- Runs with low resource usage (around 3 GB of RAM for VMs).
Conclusion:
- The model is robust, fast, and optimized for GPU acceleration but can run on CPUs as well. License is CC BY 4.0, check for commercial use terms.