alphacep / alphacep/vosk-api

False positives when using dynamic graph models

オープン
#1,339 コメント 3 件 リアクション 1 件 担当者 0 名 GitHub で見る
主要言語
Jupyter Notebook
スター
15.1k
フォーク
1.8k
PR マージ指標
30日以内にマージされた PR はありません

説明

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!!!

コントリビューションガイド

このリポジトリのコントリビューションガイドは索引されていません

評価

この issue はまだ評価されていません。

新しい issue をメールで受け取る

初心者向けの GitHub issue を短くまとめたダイジェスト。