Abstract
A system computer readable medium and method for sampling a speech signal; dividing the sampled speech signal into overlapped frames; extracting first pitch information from a frame using frequency domain analysis; providing at least one pitch candidate each being associated with a spectral score from the first pitch information each of the at least one pitch candidate representing a possible pitch estimate for the frame; extracting second pitch information from the frame using a time domain analysis; providing a correlation score for the at least one pitch candidate from the second pitch information; and selecting one of the at least one pitch candidate to represent the pitch estimate of the frame. The system computer readable medium and method are suitable for speech coding and for distributed speech recognition.
| Technology | Declaration Information | Specification Information | Explicitly Disclosed | Patent Type | |||||
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| Declaration Date | Declaration Reference | Declaring Company | Specification Number | ||||||
| 5G,4G,3G,2G | 16/12/2010 | ISLD-201101-006 | MOTOROLA INC | No | Family Member | ||||
| 5G,4G,3G,2G | 16/12/2010 | ISLD-201101-006 | MOTOROLA INC | Yes | Basis Patent | ||||
| Not Available | 16/12/2010 | ISLD-201101-006 | MOTOROLA INC | No | Family Member | ||||
| Not Available | 16/12/2010 | ISLD-201101-006 | MOTOROLA INC | Yes | Basis Patent | ||||
| Not Available | 16/12/2010 | ISLD-201101-008 | MOTOROLA INC | No | Family Member | ||||
| Not Available | 16/12/2010 | ISLD-201101-008 | MOTOROLA INC | Yes | Basis Patent | ||||
Specification Information
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Technologies
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| Publication No | Technology | Declaration Information | Specification Information | Explicitly Disclosed | Patent Type | Status | National Phase Entries | |||||
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Technologies
Signal Processing
Product
Use Cases
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Services
Claim
1. A method comprising: sampling a speech signal; dividing the sampled speech signal into overlapping frames; extracting first pitch information from a frame using frequency domain analysis; providing at least one pitch candidate, each being coupled with a spectral score, from the first pitch information, each of the at least one pitch candidate representing a possible pitch estimate for the frame ; extracting second pitch information from the frame using a time domain analysis; providing a correlation score for the at least one pitch candidate from the second pitch information; and selecting one of the at least one pitch candidate to represent the pitch estimate of the frame.
2. The method of claim 1, wherein the selecting comprises: selecting the one of the at least one pitch candidate that has the best combination of spectral score and correlation score thereby indicating the one pitch candidate with the best probability of matching the pitch of the frame.
3. The method of claim 2, wherein the selecting comprises: computing a match measure between the possible pitch estimate of each of the at least one of pitch candidate and a selected pitch estimate for a previous frame. selecting the one of the at least one pitch candidate that has the best combination of spectral score, correlation score and the match measure , thereby indicating the one pitch candidate with the best probability of matching the pitch of the frame.
4. The method of claim 1, wherein the at least one pitch candidate comprise not more than six pitch candidates representing not more than possible six pitch estimates for the frame.
5. The method of claim 1, wherein the spectral score of the at least one pitch candidate indicates a measure of compatibility of a pitch value with spectral peaks found in the spectrum of the frame.
6. The method of claim 1, wherein the extracting second pitch information from the frame using a time domain analysis comprises: combining the frame with the previous frame together into an extended frame; and computing a downsampled extended frame by low-pass filtering and down sampling the extended frame.
7. The method of claim 1, wherein the providing correlation score comprises: calculation of cross correlation between two fragments of the downsampled extended frame.
8.η The method of claim 7, wherein the two fragments are of a predefined length and are delayed relative to each other by a lag value corresponding to each of the at least one pitch candidate.
9. The method of claim 8, wherein the position of the two fragments within the downsampled extended frame is selected by maximizing the total energy of the fragments
10. The method of claim 1 , further comprising: selecting a plurality of pitch estimates of a plurality of frames of the sampled speech signal; and coding a representation of the sampled speech signal, the representation comprising the plurality of pitch estimates
11. The method of claim 10, wherein the coded representation of the sampled speech signal is used in a distributed speech recognition system
12. A distributed speech recognition system comprising: a distributed speech recognition front-end for extracting features of a speech signal, the distributed speech recognition front-end comprising: a memory; a processor, communicatively coupled with the memory; and a pitch extracting processor, communicatively coupled with the memory and the processor, for extracting pitch information from a speech signal by: sampling a speech signal; dividing the sampled speech signal into overlapped frames; extracting first pitch information from a frame using frequency domain analysis; providing at least one pitch candidate, each being coupled with a spectral score, from the first pitch information, each of the at least one pitch candidate representing a possible pitch estimate for the frame; extracting second pitch information from the frame using a time domain analysis; providing a correlation score for the at least one pitch candidate from the second pitch information; and selecting one of the at least one pitch candidate to represent the pitch estimate of the frame
13. The distributed speech recognition system of claim 12, wherein the pitch extracting processor selecting comprises: selecting the one of the at least one pitch candidate that has the best combination of spectral score and correlation score thereby indicating the one pitch candidate with the best probability of matching the pitch of the frame
14. The distributed speech recognition system of claim 13, wherein the pitch extracting processor selecting comprises: computing a match measure between the possible pitch estimate of each of the at least one of pitch candidate and a selected pitch estimate for a previous frame. selecting the one of the at least one pitch candidate that has the best combination of spectral score, correlation score and the match measure , thereby indicating the one pitch candidate with the best probability of matching the pitch of the frame
15. The distributed speech recognition system of claim 12, wherein the at least one pitch candidate comprise not more than six pitch candidates representing not more than possible six pitch estimates for the frame
16. The distributed speech recognition system of claim 12, wherein the spectral score of the at least one pitch candidate indicates a measure of compatibility of a pitch value with spectral peaks found in the spectrum of the frame
17. The distributed speech recognition system of claim 12, wherein the pitch extracting processor extracting second pitch information from the frame using a time domain analysis comprises: combining the frame with the previous frame together into an extended frame; and computing a downsampled extended frame by low-pass filtering and down sampling the extended frame
18. The distributed speech recognition system of claim 12, wherein the pitch extracting processor providing correlation score comprises: calculation of cross correlation between two fragments of the downsampled extended frame
19. The distributed speech recognition system of claim 18, wherein the two fragments are of a predefined length and are delayed relative to each other by a lag value corresponding to each of the at least one pitch candidate. 20. The distributed speech recognition system of claim 19, wherein the position of the two fragments within the downsampled extended frame is selected by maximizing the total energy of the fragments.
21. The distributed speech recognition system of claim 12, wherein the pitch extracting processor further selecting a plurality of pitch estimates of a plurality of frames of the sampled speech signal; and coding a representation of the sampled speech signal, .the representation comprising the plurality of pitch estimates.
22. A computer readable medium comprising computer instructions for a speech processing system, the computer instructions including instructions for: sampling a speech signal; dividing the sampled speech signal into overlapped frames; extracting first pitch information from a frame using frequency domain analysis; providing at least one pitch candidate, each being coupled with a spectral score, from the first pitch information, each of the at least one pitch candidate representing a possible pitch estimate for the frame ; extracting second pitch information from the frame using a time domain analysis; providing a correlation score for the at least one pitch candidate from the second pitch information; and selecting one of the at least one pitch candidate to represent the pitch estimate of the frame.
23. The computer readable medium of claim 22, wherein the selecting comprises: selecting the one of the at least one pitch candidate that has the best combination of spectral score and correlation score thereby indicating the one pitch candidate with the best probability of matching the pitch of the frame.
24. The computer readable medium of claim 22, wherein the selecting comprises: computing a match measure between the possible pitch estimate of each of the at least one of pitch candidate and a selected pitch estimate for a previous frame. selecting the one of the at least one pitch candidate that has the best combination of spectral score, correlation score and the match measure , thereby indicating the one pitch candidate with the best probability of matching the pitch of the frame.
25. The computer readable medium of claim 22, wherein the spectral score of the at least one pitch candidate indicates a measure of compatibility of a pitch value with spectral peaks found in the spectrum of the frame.
26. The computer readable medium of claim 22, wherein the extracting second pitch information from the frame using a time domain analysis comprises: combining the frame with the previous frame together into an extended frame; and computing a downsampled extended frame by low-pass filtering and down sampling the extended frame.', "27. The computer readable medium of claim 22, wherein the providing correlation score comprises: calculation of cross correlation between two fragments of the downsampled extended frame. 28. The computer readable medium of claim 27, wherein the two fragments are of a predefined length and are delayed relative to each other by a lag value con'esponding to each of the at least one pitch candidate.", '29. The computer readable medium of claim 22, wherein the computer instructions further including instructions for: selecting a plurality of pitch estimates of a plurality of frames of the sampled speech signal; and coding a representation of the sampled speech signal, the representation comprising the plurality of pitch estimates.
30. The computer readable medium of claim 29, wherein the coded representation of the sampled speech signal is for use in a distributed speech recognition system.']
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Explicitly disclosed patent:openly and comprehensibly describes all details of the invention in the patent document.
Implicitly disclosed patent:does not explicitly state certain aspects of the invention, but still allows for these to be inferred from the information provided.
Basis patent:The core patent in a family, outlining the fundamental invention from which related patents or applications originate.
Family member:related patents or applications that share a common priority or original filing.