IP Library Granted Patent US 8,527,271
Granted Patent B2
US 8,527,271 · App. 12/452,707 · Granted Sep 3, 2013

Method for speech recognition

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 8,527,271
App. No.
12/452,707
Granted
Sep 3, 2013
Kind
B2
Abstract

A method for the voice recognition of a spoken expression to be recognized, comprising a plurality of expression parts that are to be recognized. Partial voice recognition takes place on a first selected expression part, and depending on a selection of hits for the first expression part detected by the partial voice recognition, voice recognition on the first and further expression parts is executed.

Claims (33)

1. A computer-implemented method for speech recognition of a spoken expression, which comprises a first expression part and remaining expression parts to be recognized, comprising performing by a processor operations of:

conducting a partial speech recognition on the first expression part using a Hidden-Markov-Model, wherein the remaining expression parts are covered by fill data, the partial speech recognition using a first vocabulary having a list of search terms for the first expression part;

selecting N best fitting hits for the first expression part from the list of search terms;

creating a second vocabulary, different than the first vocabulary, the second vocabulary comprising a list of search term combinations depending on the selected N best fitting hits for the first expression part, the second vocabulary having a list of search term combinations that covers the remaining expression parts previously covered by the fill data;

conducting a second speech recognition on the remaining expression parts using the second vocabulary; and

providing a result, including a speech-recognized result of the first expression part and a speech-recognized result of the remaining expression parts.

2. The method according to claim 1 , wherein the first expression part is selected from the spoken expression based on a temporal energy contour of the spoken expression.

3. The method according to claim 1 , wherein the first expression part is selected from the spoken expression based on a speech activity recognition in the expression.

4. The method according to claim 1 , wherein the method recognizes the spoken expression using a hierarchically built database in which a generic city name term has further street address terms assigned thereto, and the further street address terms have even further house number subtopics are assigned thereto.

5. The method according to claim 1 , wherein after conducting the partial speech recognition, the first vocabulary is deleted from a memory and the second vocabulary is loaded into the memory.

6. The method according to claim 1 , wherein the first expression part is located at the beginning of the spoken expression.

7. The method according to claim 1 wherein at least parts of said second vocabulary are precompiled.

8. The method according to claim 1 wherein a partial vocabulary is precompiled for the second vocabulary, and reference vectors of a Hidden-Markov-Model are calculated and stored for the partial vocabulary.

9. The method according to claim 1 , wherein the list of search terms of the first vocabulary comprises a list of city names, and the list of search term combinations of the second vocabulary comprises a list of city name and street address combinations.

10. A speech recognition device to recognize a spoken expression, which comprises a first expression part and remaining expression parts to be recognized, the speech recognition device comprising:

a database including a memory and providing at least one of search terms and a phonemic transcription of the search terms; and

a control unit connected to the database and configured to:

conduct a partial speech recognition on the first expression part using a Hidden-Markov-Model, wherein the remaining expression parts are covered by fill data, the partial speech recognition using a first vocabulary having a list of search terms for the first expression part;

select N best fitting hits for the first expression part from the list of search terms;

create a second vocabulary, different than the first vocabulary, the second vocabulary comprising a list of search term combinations depending on the selected N best fitting hits for the first expression part, the second vocabulary having a list of search term combinations that covers the remaining expression parts previously covered by the fill data;

conduct a second speech recognition on the remaining expression parts using the second vocabulary; and

provide a result, including a speech-recognized result of the first expression part and a speech-recognized result of the remaining expression parts.

11. The speech recognition device according to claim 10 , wherein the speech recognition device is embedded in a motor vehicle.

12. The speech recognition device according to claim 11 , wherein said speech recognition device is part of a vehicle navigation system.

13. The speech recognition device according to claim 11 , wherein said speech recognition device is formed as a part of a mobile phone and/or of an audio player.

14. The speech recognition device according to claim 10 , wherein the list of search terms of the first vocabulary comprises a list of city names, and the list of search term combinations of the second vocabulary comprises a list of city name and street address combinations.

15. A computer readable storage medium storing a program, which when executed by a computer performs a method for speech recognition of a spoken expression, which comprises a first expression part and remaining expression parts to be recognized, the method comprising:

conducting a partial speech recognition on the first expression part using a Hidden-Markov-Model wherein the remaining expression parts are covered by fill data, the partial speech recognition using a first vocabulary having a list of search terms for the first expression part;

selecting N best fitting hits for the first expression part from the list of search terms;

creating a second vocabulary, different than the first vocabulary, the second vocabulary comprising a list of search term combinations depending on the selected N best fitting hits for the first expression part, the second vocabulary having a list of search term combinations that covers the remaining expression parts previously covered by the fill data;

conducting a second speech recognition on the remaining expression parts using the second vocabulary; and

providing a result, including a speech-recognized result of the first expression part and a speech-recognized result of the remaining expression parts.

16. The computer readable storage medium according to claim 15 , wherein the list of search terms of the first vocabulary comprises a list of city names, and the list of search term combinations of the second vocabulary comprises a list of city name and street address combinations.

Assignments (7)
RELEASE (REEL 052935 / FRAME 0584) Recorded Jan 2, 2025
From: WELLS FARGO BANK, NATIONAL ASSOCIATION
To: CERENCE OPERATING COMPANY
Reel/Frame 069797/0818 →
CORRECTIVE ASSIGNMENT TO CORRECT THE REPLACE THE CONVEYANCE DOCUMENT WITH THE NEW ASSIGNMENT PREVIOUSLY RECORDED AT REEL: 050836 FRAME: 0191. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Apr 19, 2022
From: NUANCE COMMUNICATIONS, INC.
To: CERENCE OPERATING COMPANY
Reel/Frame 059804/0186 →
SECURITY AGREEMENT Recorded Jun 15, 2020
From: CERENCE OPERATING COMPANY
To: WELLS FARGO BANK, N.A.
Reel/Frame 052935/0584 →
RELEASE OF SECURITY INTEREST Recorded Jun 12, 2020
From: BARCLAYS BANK PLC
To: CERENCE OPERATING COMPANY
Reel/Frame 052927/0335 →
SECURITY AGREEMENT Recorded Nov 7, 2019
From: CERENCE OPERATING COMPANY
To: BARCLAYS BANK PLC
Reel/Frame 050953/0133 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE NAME PREVIOUSLY RECORDED AT REEL: 050836 FRAME: 0191. ASSIGNOR(S) HEREBY CONFIRMS THE INTELLECTUAL PROPERTY AGREEMENT. Recorded Oct 29, 2019
From: NUANCE COMMUNICATIONS, INC.
To: CERENCE OPERATING COMPANY
Reel/Frame 050871/0001 →
INTELLECTUAL PROPERTY AGREEMENT Recorded Oct 23, 2019
From: NUANCE COMMUNICATIONS, INC.
To: CERENCE INC.
Reel/Frame 050836/0191 →