Comments (1)
Accuracy in the train set increased only by 2% (67.91% from 66.03%). In order to confirm that the adaptation procedure was correct, I evaluate it on the train set, giving 84.13% accuracy.
All metrics are uploaded here: https://www.dropbox.com/s/0mpn06j87dsvw6n/Metrics.xlsx?dl=0
from gsoc2019-sphinx.
Related Issues (20)
- (1) Record user's dictation and send it to backend [1]
- (0.5) Add py4j configurations to enable communication between java and python [0.5]
- (1) Connect the python system with sphinx4 java library using py4j [1]
- (1) Improve documentation in angular and flask api [1]
- (0.5) Decode speech to text using specific language model in api [0.5]
- (0.5) Display different outputs (with and without adaptation) after dictation [0.5]
- (0.2) Add very simple footer (extend it later) [0.2]
- (0.5) Show user information after sign-up [0]
- (0.5) Add option for fetching emails from a certain folder [0]
- (1) Add styling in email presentation, cluster form and cluster presentation [1]
- (0.5) Check sound quality after transfer to server cause accuracy is poor (check comment) [0.5] HOT 1
- (0.2) Add option for pocketsphinx stream recongnizer [0.2]
- (0.5) Add endpoint for mllr acoustic adaptation [0.5]
- (1) Add endpoint for saving dictations (to be used in acoustic adaptation) [1]
- (0.5) Add final text in dictation page [0.5]
- (3) Add WebSocket support in combination with Sphinx4 LiveSpeechRecognizer [0]
- (0.2) Add more info and styling in footer [0.2]
- (0.5) Add log out button and log out api endpoint [0.5]
- (2) Deployment in okeanos, installation of necessary packages [2]
- (2) Add post processing part in online system [2] HOT 1
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