How to use CLAMS apps
- Want to know how to use CLAMS apps? Check out CLAMS App user manual.
- Want a human friendly views of MMIF JSON files? Visit MMIF visualizer repository.
Detects scenes with text, like slates, chyrons and credits.
A CLAMS wrapper for Whisper-based ASR software originally developed by OpenAI.
Using EasyOCR to extract text from timeframes
Apply named entity linking to all text documents in a MMIF file.
This tool detects slates.
This tool uses a vision model to classify video segments. Currenly supports “chyron” frame type.
This tool detects SMPTE color bars.
OpenCV-based text localization app that used EAST text detection model. Please visit the source code repository for full documentation.
This tool applies Parseq OCR to a video or image and generates text boxes and OCR results.
This tool applies Tesseract OCR to a video or image and generates text boxes and OCR results.
This tool detects chyrons, generates time segments.
This CLAMS app aligns transcript and audio track using Gentle. Gentle is a robust yet lenient forced aligner built on Kaldi.This app only works when Gentle is already installed locally.Unfortunately, Gentle is not distributed as a Python package distribution.To get Gentle installation instruction, see https://lowerquality.com/gentle/ Make sure install Gentle from the git commit specified in
analyzer_version in this metadata.
Detects spans of monotonic audio within an audio file
Apply spaCy NLP to all text documents in a MMIF file.
Brandeis Acoustic Classification & Segmentation (ACS) is a audio segmentation tool developed at Brandeis Lab for Linguistics and Computation. The original software can be found at https://github.com/brandeis-llc/acoustic-classification-segmentation .
inaSpeechSegmenter is a CNN-based audio segmentation toolkit. The original software can be found at https://github.com/ina-foss/inaSpeechSegmenter .
A CLAMS wrapper for Kaldi-based ASR software originally developed by PopUpArchive and hipstas, and later updated by Kyeongmin Rim at Brandeis University. Wrapped software can be found at https://github.com/brandeis-llc/aapb-pua-kaldi-docker .