After a user selects a level, the system takes them to the labeling view for the assigned file. In the labeling view, users can listen to audio and either transcribe what they hear or edit an existing transcript.
The labeling view provides an audio player with controls that allow users to play, pause, and jump to different times in the assigned audio file.
To help improve productivity, Hotpepper provides keyboard shortcuts that allow users to manipulate the audio player without using the player controls. For example, pressing
TAB on the keyboard skips the audio player backwards by two seconds.
To see a list of available shortcuts, visit
When using the audio player, users can control the following audio settings:
The majority of the labeling view consists of a textarea that contains the transcription of the assigned file where users can add and edit text.
For files assigned at level L1, users may be able to submit the assigned file to an on-premise Deepgram Speech Engine for automatic speech recognition (ASR) and transcription. When ASR is used, the Hotpepper server sends the assigned audio file to the configured Speech API endpoint, parses a transcript from the results, and automatically populates the Transcript textarea of the labeling view with the returned transcript.
To enable this feature, Hotpepper must be configured appropriately. When Hotpepper is properly configured for ASR, the File Details area of the labeling view will include a Get ASR button.
To learn more about configuring ASR for automatic transcription, visit Hotpepper User Guide: Setting Up.
To help improve productivity, Hotpepper provides built-in macros, which allow users to type string combinations that automatically expand. For example, typing “1” (the numeral 1 with a space after it) expands to “[SPEAKER 1:]”, and typing “ty” expands to “thank you”.
To see a list of available macros, visit
While transcribing or editing a file, various file details are available to the user:
In addition, users may add notes about the file or dataset. For example, users may want to add details that may be commonly heard throughout a dataset, such as product names, people’s names, acronyms, or specialized terminology.
When labeling data, users can perform the following operations on the assigned file:
Users select Save to save the current transcript to the server and update Last Saved in the File Details. Hotpepper also periodically auto-saves transcripts.
Users select Done to mark the assigned file as finished and send it to the next level for further labeling. Once the file is submitted, the system returns the user to the dashboard, so they can select another project.
Users select Abandon to opt out of working with a file. Once a user abandons a file, the file will no longer be available to the user at any level.
By default, when a user exits the labeling view, work on the current file is paused. Users can also pause work on a file by clicking the Hotpepper icon or the browser’s back button.