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cottom /rvc-train-voice-model:fd9c2739
Input schema
The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.
| Field | Type | Default value | Description |
|---|---|---|---|
| dataset |
string
|
One recording, or a .zip of recordings (wav, mp3, flac, m4a, ogg, ...). Songs, a cappella and speech are all cleaned to the dry lead voice first. 1 minute minimum, 10+ recommended, 30 maximum.
|
|
| sample_rate |
None
|
40k
|
Model sample rate.
|
| epochs |
integer
|
0
Max: 1000 |
Training epochs. 0 picks about 4,000 steps for the cleaned dataset (100-500 epochs).
|
| batch_size |
integer
|
8
Min: 2 Max: 32 |
Segments per training step.
|
| separation |
None
|
auto
|
Vocal extraction. auto: per 10-second window, only where there is a backing track or bleed. always: everywhere. never: train on the audio as uploaded.
|
| lead_vocal_only |
None
|
auto
|
Remove harmonies and backing vocals (the main cause of cracked, hoarse notes). auto: wherever a backing track was found.
|
| remove_reverb |
boolean
|
True
|
Remove reverb and echo (the second cause of cracked notes).
|
| denoise |
boolean
|
True
|
Gate steady noise (hiss, hum) against the recording's quietest moments.
|
| remove_breaths |
boolean
|
True
|
Silence breaths: quiet unvoiced stretches longer than a consonant.
|
| residue_floor_db |
number
|
-50
Min: -90 Max: -30 |
Delete spectral content this far below the voice (separation residue). -90 keeps everything.
|
| time_limit_minutes |
number
|
28
Min: 10 Max: 180 |
Whole-run budget. Training stops early, keeping its latest saved weights, to finish inside it. Replicate stops a prediction after 30 minutes of running.
|
Output schema
The shape of the response you’ll get when you run this model with an API.
Schema
{'items': {'format': 'uri', 'type': 'string'},
'title': 'Output',
'type': 'array'}