What the data for this category looks like
Core data for speech annotation and transcription scenarios originates from audio files, annotation platforms, proprietary vocabularies, and spot-check samples. Documents used for daily operations include transcription specifications, audio lists, quality inspection reports, and speaker annotation forms. Data updates occur on a daily schedule or per batch of annotation tasks. Core fields include audio duration, speaker ID, transcribed text, quality inspection scores, and other relevant items. This category first converts audio content to structured text before conducting annotation verification. This differs from the pre-processing logic of text annotation projects.
Constraints on permission and data isolation from these characteristics
Data for this category is associated with multiple sensitive resources, including undisclosed proprietary vocabularies, undelivered audio files, and quality inspection reports. Permission isolation must align with business division of labor. Dividing permissions by annotation team and quality inspection roles prevents cross-team data leaks. The batch-based data update feature requires permission configurations to be dynamically bound to task batches. This prevents old permissions from overwriting new task data. Speaker annotation forms contain personal identity information. Access must be restricted to only the algorithm team and quality inspection personnel. This prevents tampering with annotation data.
How to configure settings
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
teamId permission grouping | Assign a unique teamId to each annotation team | Speech annotation tasks are divided by team, which matches team-level data isolation requirements |
| Role permission granularity | Set three-level roles: annotator, quality inspector, algorithm team | Different roles have different document access scopes; annotators may only view assigned audio lists |
tmbId task binding | Bind a unique tmbId to each annotation batch | Isolate data by task batch to prevent unauthorized cross-batch access |
| Sensitive document access restrictions | Only allow administrators and the algorithm team to access transcription specifications and proprietary vocabularies | These documents contain business-specific rules and require strict isolation |
| Single data access limit | Restrict to the first 100 audio files | Prevent unauthorized bulk pulling of full annotation datasets |
| Quality inspection result modification permission | Only allow quality inspectors and administrators to modify quality inspection reports | Quality inspection results directly impact delivery quality, so unauthorized modifications must be restricted |
Three common configuration errors
- Symptom: An API call bound to a specified
teamIdreturns an "no permission" error. Cause: The caller is not bound to the correspondingteamId, so access to the specified team's annotation data is blocked. - Symptom: Regular annotators can view audio lists from other teams. Cause: Unique
teamIdassignments are not implemented per team, so cross-team permission isolation is not configured. - Symptom: Unauthorized annotators modify transcription specifications. Cause: Access roles for sensitive documents are not restricted, and transcription specifications are open to all roles.
How to verify successful configuration
- Log in to the system as an annotator role, attempt to access audio lists from other teams, and confirm that the content cannot be viewed.
- Call an API bound to a specified
teamIdandtmbId, and verify that only annotation data for the current team and batch can be retrieved. - Attempt to modify transcription specifications, and confirm that only administrators and the algorithm team can perform this action.
- Check permission bindings for task batches, and confirm that only audio and annotation data from the current batch can be accessed.
The values provided here are common starting points, and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.