IP Library Granted Patent US 6,904,405
Granted Patent B2
US 6,904,405 · App. 10/061,052 · Granted Jun 7, 2005

Message recognition using shared language model

View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 6,904,405
App. No.
10/061,052
Granted
Jun 7, 2005
Kind
B2
Abstract

Certain disclosed methods and systems perform multiple different types of message recognition using a shared language model. Message recognition of a first type is performed responsive to a first type of message input (e.g., speech), to provide text data in accordance with both the shared language model and a first model specific to the first type of message recognition (e.g., an acoustic model). Message recognition of a second type is performed responsive to a second type of message input (e.g., handwriting), to provide text data in accordance with both the shared language model and a second model specific to the second type of message recognition (e.g., a model that determines basic units of handwriting conveyed by freehand input). Accuracy of both such message recognizers can be improved by user correction of misrecognition by either one of them. Numerous other methods and systems are also disclosed.

Claims (41)

1. A system for generating text responsive to message input of a first type and a second type, the system comprising:

(a) a unified message model including:

(1) a shared language model;

(2) a first model specific to a first type of message recognition; and

(3) a second model specific to a second type of message recognition;

(b) a first message recognizer, responsive to the first type of message input to provide text data in accordance with both the shared language model and the first model; and

(c) a second message recognizer, responsive to the second type of message input to provide text data in accordance with both the shared language model and the second model; wherein

(d) the shared language model is trainable responsive to user correction of misrecognition by either of the first and second message recognizers, thereby improving accuracy of each of the first and second message recognizers.

2. The system of claim 1 wherein:

(a) the first type of message recognition is speech recognition, the first type of message input is voice input, and the first model is an acoustic model; and

(b) the second type of message recognition is handwriting recognition, the second type of message input is freehand input, and the second model is a handwriting model.

3. The system of claim 2 further comprising a stylus, wherein the shared language model is trainable responsive to user correction of misrecognition by the first message recognizer by (a) movement of the stylus across visual indicia of dictated text that has been erroneously generated to specify a selection from the text, and (b) correction of the selection.

4. The system of claim 3 wherein:

(a) the stylus includes a pointing interface and a microphone;

(b) the system further comprises a tablet responsive to the pointing interface;

(c) the voice input is from the microphone; and

(d) the freehand input is from the pointing interface being manually manipulated on the tablet.

5. The system of claim 4 wherein the visual indicia of dictated text appears on the tablet.

6. The system of claim 1 wherein the shared language model comprises a syntactic model and a semantic model.

7. A method for performing message recognition with a shared language model, the method comprising:

(a) performing message recognition of a first type, responsive to a first type of message input, to provide text data in accordance with both the shared language model and a first model specific to the first type of message recognition;

(b) performing message recognition of a second type, responsive to a second type of message input, to provide text data in accordance with both the shared language model and a second model specific to the second type of message recognition; and

(c) training the shared language model responsive to user correction of error in message recognition of either of the first and second types, thereby improving accuracy of each of the first arid second types of message recognition.

8. The method of claim 7 wherein:

(a) performing the first type of message recognition comprises performing speech recognition responsive to voice input in accordance with the shared language model and a first model that is an acoustic model; and

(b) performing the second type of message recognition comprises performing handwriting recognition responsive to freehand input in accordance with the shared language model and a second model that is a handwriting model.

9. The method of claim 8 wherein training the shared language model includes (a) moving a stylus across visual indicia of dictated text that has been erroneously generated to specify a selection from the text, and (b) correcting the selection.

10. The method of claim 9 wherein:

(a) performing speech recognition responsive to voice input includes responding to voice input from a microphone in the stylus; and

(b) performing handwriting recognition responsive to freehand input includes responding to manual manipulation of the stylus on a tablet.

11. The method of claim 10 wherein the visual indicia of dictated text appears on the tablet.

12. The method of claim 7 wherein performing message recognition in accordance with the shared language model comprises performing message recognition in accordance with a syntactic model and a semantic model.

13. A system for performing message recognition with a trainable shared language model, the system comprising:

(a) means for performing message recognition of a first type, responsive to a first type of message input, to provide text data in accordance with both the shared language model and a first model specific to the first type of message recognition; and

(b) means for performing message recognition of a second type, responsive to a second type of message input, to provide text data in accordance with both the shared language model and a second model specific to the second type of message recognition.

14. The system of claim 13 wherein:

(a) the first type of message recognition is speech recognition, the first type of message input is voice input, and the first model is an acoustic model; and

(b) the second type of message recognition is handwriting recognition, the second type of message input is freehand input,. and the second model is a handwriting model.

15. The system of claim 13 wherein the shared language model comprises a syntactic model and a semantic model.

16. The system of claim 13 further comprising means for training the shared language model responsive to user correction of error in message recognition of either of the first and second types, thereby improving accuracy of each of the first and second types of message recognition.

17. The system of claim 16 wherein the means for training the shared language model includes means for (a) specifying a selection from visual indicia of dictated text that has been erroneously generated, and (b) correcting the selection.

Assignments (6)
SECURITY INTEREST Recorded Jul 14, 2022
From: BUFFALO PATENTS, LLC
To: INTELLETUAL VENTURES ASSETS 90 LLC; INTELLECTUAL VENTURES ASSETS 167 LLC
Reel/Frame 060654/0338 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 26, 2021
From: INTELLECTUAL VENTURES ASSETS 167 LLC
To: BUFFALO PATENTS, LLC
Reel/Frame 056978/0949 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 14, 2021
From: XYLON LLC
To: INTELLECTUAL VENTURES ASSETS 167 LLC
Reel/Frame 056537/0029 →
MERGER Recorded Oct 26, 2015
From: OPTICAL RESEARCH PARTNERS LLC
To: XYLON LLC
Reel/Frame 036954/0110 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 29, 2005
From: MOUNT HAMILTON PARTNERS, LLC
To: OPTICAL RESEARCH PARTNERS LLC
Reel/Frame 016202/0961 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 12, 2005
From: SUOMINEN, EDWIN A
To: MOUNT HAMILTON PARTNERS, LLC
Reel/Frame 016010/0010 →