Summary
Starting with TRBOnet 6.5, voice transmissions can be converted to text using AI language models. Two methods are supported: OpenAI commercial service and a self-hosted Local deployment. Transcription runs in real time or retrospectively in reports. Quality depends on the selected language model.
Do not install the local model on the same computer running TRBOnet. Local models impose heavy system load. Use a dedicated computer built for the model.
Speech to Text Processing
1. The server receives or sends a voice transmission.
2. The server removes silence segments from the transmission.
3. The server sends the prepared audio file to the language model using the endpoint
/v1/audio/transcriptions.
4. The language model receives and processes the file.
5. The language model returns the transcribed text to TRBOnet.
Model Types
| Method | Model | Endpoint |
|---|---|---|
| OpenAI API key | Whisper-1 | OpenAI servers |
| Local | v1 compatible LLM model with audio support | Self-hosted |
OpenAI Model
Model: Whisper-1
Configuration: Enter the purchased API key in . Requests are sent to OpenAI servers.
TRBOnet Demo and Trial license includes a pre-configured OpenAI Whisper test connection. This function is unavailable with Commercial license.
Local Model
Use any model compatible with v1 API. Deploy using publicly available solutions such as LocalAI.
•Tested models: Whisper-1, Gemma-4.Setup
1. Deploy the Local model (Example: https://github.com/mudler/LocalAI).
2. Add the language model.
3. Go to .
4. In , enter the model name (example: Gemma-4).
5. In , enter the Local Model server address:
https://XXX.XXX.XXX.XXX/v1/audio/transcriptions.
6. In , enter the key configured in the Local model. If no API key is set up in the Local model, enter any text in this field.
7. In , select the language that system users will speak. This setting controls the language the model expects in audio input and uses for text output.
The language setting is required. Transcription accuracy depends on matching the selected language to the actual speech in transmissions.
For detailed configuration options and output example, see the following sections in the TRBOnet user manual:
• 6.4.5.15 AI Speech to Text - administration settings for the feature
• 6.5.8.3 Speech to Text - user-facing speech to text functionality
• 6.10 Voice Recording - voice recording and transcript integration
Recommendations
•Use a language model suitable for the speaker language. Some models provide better transcription for a specific language.
•Load models into GPU video memory (VRAM) for faster performance. Alternatively, use dedicated hardware solutions tailored for AI operation.
•Test the local model under high load to determine acceptable performance.
•Neocom Software does not provide hardware specifications. Requirements depend on the model and load level.