SPEECH ENDPOINTING BASED ON WORD COMPARISONS

• US 20150310879A1
• Filed: 04/08/2015
• Published: 10/29/2015
• Est. Priority Date: 04/23/2014
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Buchanan, Michael, Gupta, Pravir Kumar, Tandiono, Christopher Bo
• Granted Patent: US 9,607,613 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 40/216 using statistical methods
• CPC Class Codes: G06F 40/253 Grammatical analysis; Style critique
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: G10L 15/04 Segmentation; Word boundary detection
• CPC Class Codes: G10L 15/05 Word boundary detection
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G10L 17/06 Decision making techniques; Pattern matching strategies
• CPC Class Codes: G10L 2015/088 Word spotting
• CPC Class Codes: G10L 2015/223 Execution procedure of a spoken command
• CPC Class Codes: G10L 2025/783 based on threshold decision
• CPC Class Codes: G10L 25/51 for comparison or discrimination
• CPC Class Codes: G10L 25/78 Detection of presence or absence of voice signals switching of direction of transmission by voice frequency in two-way loud-speaking telephone systems H04M9/10
• CPC Class Codes: G10L 25/87 Detection of discrete points within a voice signal
• CPC Class Codes: G10L 25/90 Pitch determination of speech signals

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech endpointing based on word comparisons are described. In one aspect, a method includes the actions of obtaining a transcription of an utterance. The actions further include determining, as a first value, a quantity of text samples in a collection of text samples that (i) include terms that match the transcription, and (ii) do not include any additional terms. The actions further include determining, as a second value, a quantity of text samples in the collection of text samples that (i) include terms that match the transcription, and (ii) include one or more additional terms. The actions further include classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value.

Claims

1. A computer-implemented method comprising:

obtaining a transcription of an utterance;

determining, as a first value, a quantity of text samples in a collection of text samples that (i) include terms that match the transcription, and (ii) do not include any additional terms;

determining, as a second value, a quantity of text samples in the collection of text samples that (i) include terms that match the transcription, and (ii) include one or more additional terms; and

classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value.

2. The method of claim 1, wherein determining, as a first value, a quantity of text samples in a collection of text samples that (i) include terms that match the transcription, and (ii) do not include any additional terms comprises:

determining that, in each text sample, that terms that match the transcription occur in a same order as in the transcription.

3. The method of claim 1, wherein determining, as a second value, a quantity of text samples in the collection of text samples that (i) include terms that match the transcription, and (ii) include one or more additional terms comprises:

determining that, in each text sample, the terms that match the transcription occur at a prefix of each text sample.

4. The method of claim 1, wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises:

determining a ratio of the first value to the second value;

determining that the ratio satisfies a threshold ratio; and

based on determining that the ratio satisfies the threshold ratio, classifying the utterance as a likely incomplete utterance.

5. The method of claim 1, comprising:

wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises classifying the utterance as a likely incomplete utterance; and

based on classifying the utterance as a likely incomplete utterance, maintaining a microphone in an active state to receive an additional utterance.

6. The method of claim 1, comprising:

wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises classifying the utterance as not a likely incomplete utterance; and

based on classifying the utterance as not a likely incomplete utterance, deactivating a microphone.

7. The method of claim 1, comprising:

receiving data indicating that the utterance is complete;

wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises classifying the utterance as a likely incomplete utterance; and

based on classifying the utterance as a likely incomplete utterance, overriding the data indicating that the utterance is complete.

8. A system comprising:

one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising;

obtaining a transcription of an utterance;

determining, as a first value, a quantity of text samples in a collection of text samples that (i) include terms that match the transcription, and (ii) do not include any additional terms;

determining, as a second value, a quantity of text samples in the collection of text samples that (i) include terms that match the transcription, and (ii) include one or more additional terms; and

classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value.

9. The system of claim 8, wherein determining, as a first value, a quantity of text samples in a collection of text samples that (i) include terms that match the transcription, and (ii) do not include any additional terms comprises:

determining that, in each text sample, that terms that match the transcription occur in a same order as in the transcription.

10. The system of claim 8, wherein determining, as a second value, a quantity of text samples in the collection of text samples that (i) include terms that match the transcription, and (ii) include one or more additional terms comprises:

determining that, in each text sample, the terms that match the transcription occur at a prefix of each text sample.

11. The system of claim 8, wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises:

determining a ratio of the first value to the second value;

determining that the ratio satisfies a threshold ratio; and

based on determining that the ratio satisfies the threshold ratio, classifying the utterance as a likely incomplete utterance.

12. The system of claim 8, the operations further comprising:

wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises classifying the utterance as a likely incomplete utterance; and

based on classifying the utterance as a likely incomplete utterance, maintaining a microphone in an active state to receive an additional utterance.

13. The system of claim 8, the operations further comprising:

wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises classifying the utterance as not a likely incomplete utterance; and

based on classifying the utterance as not a likely incomplete utterance, deactivating a microphone.

14. The system of claim 8, the operations further comprising:

receiving data indicating that the utterance is complete;

wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises classifying the utterance as a likely incomplete utterance; and

based on classifying the utterance as a likely incomplete utterance, overriding the data indicating that the utterance is complete.

15. A computer implemented method comprising:

obtaining a transcription of an utterance;

determining whether, in a collection of text samples, the utterance more often matches (i) text samples that include terms that match the transcription and that do not include any additional terms than the utterance matches, or (ii) text samples that include terms that match the transcription and that do include one or more additional terms than the utterance matches; and

determining whether the utterance is likely incomplete based on the determination.

16. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:

obtaining a transcription of an utterance;

determining, as a first value, a quantity of text samples in a collection of text samples that (i) include terms that match the transcription, and (ii) do not include any additional terms;

determining, as a second value, a quantity of text samples in the collection of text samples that (i) include terms that match the transcription, and (ii) include one or more additional terms; and

classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value.

17. The medium of claim 16, wherein determining, as a second value, a quantity of text samples in the collection of text samples that (i) include terms that match the transcription, and (ii) include one or more additional terms comprises:

determining that, in each text sample, the terms that match the transcription occur at a prefix of each text sample.

18. The medium of claim 16, wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises:

determining a ratio of the first value to the second value;

determining that the ratio satisfies a threshold ratio; and

based on determining that the ratio satisfies the threshold ratio, classifying the utterance as a likely incomplete utterance.

19. The medium of claim 16, the operations further comprising:

wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises classifying the utterance as a likely incomplete utterance; and

based on classifying the utterance as a likely incomplete utterance, maintaining a microphone in an active state to receive an additional utterance.

20. The medium of claim 16, the operations further comprising:

receiving data indicating that the utterance is complete;

wherein classifying the utterance as a likely incomplete utterance or not a likely incomplete utterance based at least on comparing the first value and the second value comprises classifying the utterance as a likely incomplete utterance; and

based on classifying the utterance as a likely incomplete utterance, overriding the data indicating that the utterance is complete.