Automatic speech recognition (ASR) is at the core of what we do at Gong. Our Revenue Intelligence platform empowers sales leaders to close more deals and manage their pipeline better as we capture customer interactions, analyze what was said and deliver data-driven insights. Building upon the tremendous advances ASR has made in the past decade, we can now process human conversations using ML and NLP algorithms easier and more effectively than ever before. However, most of these algorithms still rely on huge amounts of annotated data. That’s why we are proud to present Gecko, a new open-source tool we developed at Gong for annotating human conversations.
Meet Gecko
Gecko (github.com/gong-io/gecko) is an open-source tool for the annotation of the linguistic content of conversations. It can be used for segmentation, diarization, and transcription. With Gecko, you can create and perfect audio-based datasets, compare the results of multiple models simultaneously, and highlight differences between transcriptions. Gecko is a standalone web-based JavaScript application that runs on both desktop and mobile devices without requiring a server, making it easy to use and update.
The Gecko interface, which was designed to be clean yet interactive, integrates media player and editing capabilities. The main view features a waveform display of the audio file, a video player display if a video file was uploaded, on which the segmentation and speaker identification is overlaid and color coded. If a transcript was uploaded, it is synced with the audio so that the word currently heard in the audio playback is highlighted. You can zoom in and out of the waveform display and use the auto-center button to automatically center the waveform on the section currently playing. The Segment Labeling box shows the list of labels and allows you to add additional labels.
How to Use Gecko
