Whisper Transcribe
This component transcribes audio from a video stream.
Component Configuration
| Option | Description | Required | Environment override |
|---|---|---|---|
id |
A unique identifier for the component instance |
✓ |
|
displayName |
The name shown in the Studio UI of this component |
✓ |
|
model |
The ggml model path |
✓ |
|
language |
Source language (otherwise automatic) |
✗ |
|
translate |
Whether to translate the output to English (default: false) |
✗ |
|
tinyDiarize |
Enable tiny-diarize (speaker-turn detection). Only supported by tdrz models |
✗ |
|
initialPrompt |
Initial prompt to prime the model with expected names, jargon or style. Max ~224 tokens, and prepended to any context from previous chunks |
✗ |
|
contextPrompt |
Prompt each chunk with the tokens recognised in the previous chunk. Off by default, relying only on chunk overlap to resolve partial words |
✗ |
|
suppressNonSpeechTokens |
Suppress non-speech tokens such as [music] and [laughter] |
✗ |
|
vad |
Voice activity detection - use a silero VAD model to skip non-speech audio. Leave unset to disable |
✗ |
|
stepMs |
Audio accumulated before each transcription step (default 3000ms). Lowering this reduces latency but also throughput - if a step is not clearly faster than real time, the workflow will back up |
✗ |
|
keepMs |
Audio kept when clearing the buffer, to allow partial-word recognition (default 400ms) |
✗ |
|
useGpu |
Use GPU if available. This may move load from CPU to GPU rather than increasing throughput (default: true) |
✗ |
|
numThreads |
Number of threads to use. Using a large number of threads rarely improves performance |
✗ |
|
samplingStrategy |
Decoder sampling strategy (default greedy) |
✓ |
|
maxTokens |
Max tokens per segment (0 = no limit) |
✗ |
|
initialTemperature |
The initial decoding temperature, between 0 and 1 (default 0.0) |
✗ |
|
temperatureIncrement |
The increment of temperature on fallback, between 0 and 1 (default 0.2). Set to 0 to disable fallback |
✗ |
|
noFallback |
Do not use temperature fallback while decoding |
✗ |
|
entropyThreshold |
Entropy threshold for decoder fail, similar to OpenAI's compression_ratio_threshold (default 2.4) |
✗ |
|
logProbThreshold |
Log probability threshold for decoder fail (default -1.0) |
✗ |
|
noSpeechThreshold |
No speech threshold (default 0.6) |
✗ |
|
notes |
Notes about this component |
✗ |
Vad
| Option | Description | Required |
|---|---|---|
model |
Path to the GGML-format silero-vad model, e.g. from https://huggingface.co/ggml-org/whisper-vad |
✓ |
threshold |
Probability threshold to consider as speech (default 0.5) |
✗ |
minSpeechDurationMs |
Min duration for a valid speech segment (default 250ms) |
✗ |
minSilenceDurationMs |
Min silence duration to consider speech as ended (default 100ms) |
✗ |
maxSpeechDurationS |
Max duration of a speech segment before forcing a new segment (default unlimited) |
✗ |
speechPadMs |
Padding added before and after speech segments (default 30ms) |
✗ |
samplesOverlap |
Overlap in seconds when copying audio samples from a speech segment (default 0.1) |
✗ |