Invention Grant
- Patent Title: Efficient connectionist temporal classification for binary classification
-
Application No.: US15894872Application Date: 2018-02-12
-
Publication No.: US10762417B2Publication Date: 2020-09-01
- Inventor: Saeed Mosayyebpour Kaskari , Trausti Thormundsson , Francesco Nesta
- Applicant: SYNAPTICS INCORPORATED
- Applicant Address: US CA San Jose
- Assignee: SYNAPTICS INCORPORATED
- Current Assignee: SYNAPTICS INCORPORATED
- Current Assignee Address: US CA San Jose
- Agency: Haynes and Boone, LLP
- Main IPC: G10L15/00
- IPC: G10L15/00 ; G06N3/04 ; G06N3/08 ; G10L15/16 ; G10L15/06 ; G10L15/22

Abstract:
A classification system and method for training a neural network includes receiving a stream of segmented, labeled training data having a sequence of frames, computing a stream of input features data for the sequence of frames, and generating neural network outputs for the sequence of frames in a forward pass through the training data and in accordance weights and biases. The weights and biases are updated in a backward pass through the training data, including determining Region of Target (ROT) information from the segmented, labeled training data, computing modified forward and backward variables based on the neural network outputs and the ROT information, deriving a signal error for each frame within the sequence of frames based on the modified forward and backward variables, and updating the weights and biases based on the derived signal error. An adaptive learning module is provided to improve a convergence rate of the neural network.
Public/Granted literature
- US20180232632A1 EFFICIENT CONNECTIONIST TEMPORAL CLASSIFICATION FOR BINARY CLASSIFICATION Public/Granted day:2018-08-16
Information query