False positives when using dynamic graph models
- Lingua principale
- Jupyter Notebook
- Stelle
- 15.1k
- Fork
- 1.8k
- Metriche di merge delle PR
- Nessuna PR unita negli ultimi 30g
Descrizione
Hi!
I'm using **vosk-model-small-en-us-0.15** model and providing grammar in runtime (e.g. `["nose", "teeth", "hair", "[unk]"]`).
The issue I'm experiencing is a lot of false positives. When using the model without grammar "restrictions", although confusing some words with very similar pronunciation (e.g. two -> to), it does have a good accuracy. However, once I set the grammar, I experience several false positives (e.g. saying "cheek" returns "teeth").
As far as I have read, the only proposed workaround is to filter the recognized words by the confidence, but many times it returns a false positive with conf=1. I have also tried to modify the `acoustic-scale` and `lattice-beam` parameters of the recognizer, but it still fails a lot (although increasing the lattice beam and decreasing a little bit the acoustic scale makes a small improvement).
Is there anyone that has also experienced this and found a valid solution?
Thanks in advance!!!
Guida per i contributori
Nessuna guida per i contributori indicizzata per questo repository
Valutazione
Questa issue non è ancora stata valutata.