IP Library Granted Patent US 11,416,687
Granted Patent B2
US 11,416,687 · App. 17/017,510 · Granted Aug 16, 2022

Method and apparatus for recognizing speech

Inventors: Yumei Zhang (Beijing, CN); Gui He (Beijing, CN); Jin Hu (Beijing, CN)
Assignee: APOLLO INTELLIGENT CONNECTIVITY (BEIJING) TECHNOLOGY CO., LTD.
G06F40/30G06F40/205G10L15/22
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Quick Facts
Patent No.
US 11,416,687
App. No.
17/017,510
Granted
Aug 16, 2022
Kind
B2
Abstract

Embodiments of the present disclosure provide a method and apparatus for recognizing speech. An embodiment of the method includes: in response to detecting a speech frame, converting the speech frame into a current text in real time; in response to there being no previously saved historical text, inputting the current text into a semantic parsing model to obtain a parsing result; in response to the parsing result including a valid intention slot, ending a speech endpoint detection to complete the recognition; and outputting an instruction corresponding to the valid intention slot.

Claims (62)

1. A method for recognizing speech, the method comprising:

in response to detecting a speech frame of the speech, converting the speech frame into a current text in real time;

in response to there being no previously saved historical text, inputting the current text into a semantic parsing model to obtain a parsing result;

in response to the parsing result including a valid intention slot, ending a speech endpoint detection to complete recognizing the speech; and

outputting an instruction corresponding to the valid intention slot.

2. The method according to claim 1 , wherein the method further comprises:

in response to the parsing result not including the valid intention slot, saving the current text as a historical text and continuing to detect a new speech frame of the speech, and delaying a time of the speech endpoint detection.

3. The method according to claim 1 , wherein the method further comprises:

in response to there being a previously saved historical text, inputting the current text and the historical text into the semantic parsing model to obtain a new parsing result;

in response to the new parsing result not including the valid intention slot, merging the current text into the historical text for saving, continuing to detect a new speech frame of the speech, and delaying a time of the speech endpoint detection; and

in response to the new parsing result including the valid intention slot, ending the speech endpoint detection to complete recognizing the speech, and clearing the historical text.

4. The method according to claim 3 , wherein the inputting the current text and the historical text into the semantic parsing model comprises:

splicing the current text and the historical text; and

in response to the splicing being successful, inputting a new text obtained by splicing the current text and the historical text into the semantic parsing model to obtain the new parsing result.

5. The method according to claim 4 , wherein the inputting the current text and the historical text into the semantic parsing model comprises:

in response to the splicing failing, resetting the historical text to be the current text, and inputting only the current text into the semantic parsing model.

6. The method according to claim 1 , wherein the method further comprises:

in response to the parsing result including the valid intention slot and being a fixed result, using the parsing result as a cache instruction, and storing a corresponding relationship;

in response to acquiring a text to be parsed, matching the text to be parsed with the current text in the correspondence relationship table; and

in response to the matching being successful, directly returning the cache instruction corresponding to the current text without using the semantic parsing model.

7. An apparatus for recognizing speech, comprising:

at least one processor; and

a memory storing instructions, the instructions when executed by the at least one processor, cause the at least one processor to perform operations, the operations comprising:

converting a speech frame of the speech into a current text in real time in response to detecting the speech frame;

inputting the current text into a semantic parsing model to obtain a parsing result, in response to there being no previously saved historical text;

ending a speech endpoint detection to complete recognizing the speech, in response to the parsing result including a valid intention slot; and

outputting an instruction corresponding to the valid intention slot.

8. The apparatus according to claim 7 , wherein the operations further comprise:

in response to the parsing result not including the valid intention slot, saving the current text as a historical text and continuing to detect a new speech frame of the speech, and delaying a time of the speech endpoint detection.

9. The apparatus according to claim 7 , wherein the operations further comprise:

in response to there being a previously saved historical text, inputting the current text and the historical text into the semantic parsing model to obtain a new parsing result;

in response to the new parsing result not including the valid intention slot, merging the current text into the historical text for saving, continuing to detect a new speech frame of the speech, and delaying a time of the speech endpoint detection; and

in response to the new parsing result including the valid intention slot, ending the speech endpoint detection to complete recognizing the speech, and clearing the historical text.

10. The apparatus according to claim 9 , wherein the inputting the current text and the historical text into the semantic parsing model comprises:

splicing the current text and the historical text; and

in response to the splicing being successful, inputting a new text obtained by splicing the current text and the historical text into the semantic parsing model to obtain the new parsing result.

11. The apparatus according to claim 10 , wherein the inputting the current text and the historical text into the semantic parsing model comprises:

in response to the splicing failing, resetting the historical text to be the current text, and inputting only the current text into the semantic parsing model.

12. The apparatus according to claim 7 , wherein the operations further comprise:

in response to the parsing result including the valid intention slot and being a fixed result, using the parsing result as a cache instruction, and storing a corresponding relationship between the cache instruction and the current text into a correspondence relationship table;

in response to acquiring a text to be parsed, matching the text to be parsed with the current text in the correspondence relationship table; and

in response to the matching being successful, directly returning the cache instruction corresponding to the current text without using the semantic parsing model.

13. A non-transitory computer readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, causes the processor to perform operations, the operations comprising:

in response to detecting a speech frame of a speech, converting the speech frame into a current text in real time;

in response to there being no previously saved historical text, inputting the current text into a semantic parsing model to obtain a parsing result;

in response to the parsing result including a valid intention slot, ending a speech endpoint detection to complete recognizing the speech; and

outputting an instruction corresponding to the valid intention slot.

14. The medium according to claim 13 , wherein the operations further comprise:

in response to the parsing result not including the valid intention slot, saving the current text as a historical text and continuing to detect a new speech frame of the speech, and delaying a time of the speech endpoint detection.

15. The medium according to claim 13 , wherein the operations further comprise:

in response to there being a previously saved historical text, inputting the current text and the historical text into the semantic parsing model to obtain a new parsing result;

in response to the new parsing result not including the valid intention slot, merging the current text into the historical text for saving, continuing to detect a new speech frame of the speech, and delaying a time of the speech endpoint detection; and

in response to the new parsing result including the valid intention slot, ending the speech endpoint detection to complete recognizing the speech, and clearing the historical text.

16. The medium according to claim 15 , wherein the inputting the current text and the historical text into the semantic parsing model comprises:

splicing the current text and the historical text; and

in response to the splicing being successful, inputting a new text obtained by splicing the current text and the historical text into the semantic parsing model to obtain the new parsing result.

17. The medium according to claim 16 , wherein the inputting the current text and the historical text into the semantic parsing model comprises:

in response to the splicing failing, resetting the historical text to be the current text, and inputting only the current text into the semantic parsing model.

18. The medium according to claim 13 , wherein the operations further comprise:

in response to the parsing result including the valid intention slot and being a fixed result, using the parsing result as a cache instruction, and storing a corresponding relationship between the cache instruction and the current text into a correspondence relationship table;

in response to acquiring a text to be parsed, matching the text to be parsed with the current text in the correspondence relationship table; and

in response to the matching being successful, directly returning the cache instruction corresponding to the current text without using the semantic parsing model.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 13, 2021
From: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.
To: APOLLO INTELLIGENT CONNECTIVITY (BEIJING) TECHNOLOGY CO., LTD.
Reel/Frame 057789/0357 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 28, 2021
From: ZHANG, YUMEI; HE, GUI; HU, JIN
To: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.
Reel/Frame 055060/0831 →
Priority Claims (1)
CN 202010143037.5 · Mar 4, 2020 · national
Continuity (1)
Related Publication 20210279418A1 · Sep 9, 2021