Invention Grant
- Patent Title: Lattice decoding and result confirmation using recurrent neural networks
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Application No.: US15091871Application Date: 2016-04-06
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Publication No.: US10210862B1Publication Date: 2019-02-19
- Inventor: Faisal Ladhak , Ankur Gandhe , Markus Dreyer , Ariya Rastrow , Björn Hoffmeister , Lambert Mathias
- Applicant: Amazon Technologies, Inc.
- Applicant Address: US WA Seattle
- Assignee: Amazon Technologies, Inc.
- Current Assignee: Amazon Technologies, Inc.
- Current Assignee Address: US WA Seattle
- Agency: Pierce Atwood LLP
- Main IPC: G06F17/20
- IPC: G06F17/20 ; G10L15/00 ; G10L15/16 ; G10L19/038 ; G06N3/04

Abstract:
Neural networks may be used in certain automatic speech recognition systems. To improve performance at these neural networks, the present system converts the lattice into a matrix form, thus maintaining certain information included in the lattice that might otherwise be lost while also placing the lattice in a form that may be manipulated by other components to perform operations such as checking ASR results. The matrix representation of the lattice may be transformed into a vector representation by calculations performed at a recurrent neural network (RNN). By representing the lattice as a vector representation the system may perform additional operations, such as ASR results confirmation.
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