Method and apparatus for speech recognition
First Claim
1. A computer implemented method of comparing a series of observations representing unknown speech, to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, the method comprising the steps of:
- a) comparing two or more of the observations in one of the blocks of observations representing unknown speech, to a subset comprising one or more of the models representing known speech, to determine a likelihood of a match to each of the one or more models;
b) repeating step a) for models other than those in the subset; and
c) repeating steps a) and b) for a different one of the blocks, and thereby recognizing the unknown speech in terms of the known speech.
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Abstract
Comparing a series of observations representing unknown speech, to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, is carried out in an order which makes better use of memory. First, the observations in one of the blocks are compared (31), to a subset comprising one or more of the models, to determine a likelihood of a match to each of the one or more models. This step is repeated (33) for models other than those in the subset; and the whole process is repeated (34) for each block.
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Citations
21 Claims
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1. A computer implemented method of comparing a series of observations representing unknown speech, to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, the method comprising the steps of:
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a) comparing two or more of the observations in one of the blocks of observations representing unknown speech, to a subset comprising one or more of the models representing known speech, to determine a likelihood of a match to each of the one or more models; b) repeating step a) for models other than those in the subset; and c) repeating steps a) and b) for a different one of the blocks, and thereby recognizing the unknown speech in terms of the known speech. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer implemented method of recognising patterns in a series of observations representing unknown speech, by comparing the observations to stored models representing known speech, using a processing system having a main memory for storing the models and a cache memory, the cache memory being too small to contain all the models and observations, the series of observations being divided into blocks of at least two observations, the method comprising the steps of:
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a) using the processor to compare a subset of the models representing known speech to the observations, representing unknown speech, in one of the blocks of observations, to recognise the patterns, the subset of the models being small enough to fit in the cache memory; b) repeating step a) for a different subset of the modelsi and c) repeating steps a) and b) for a different one of the blocks, and thereby recognizing the unknown speech in terms of the known speech.
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11. A computer implemented method of recognising patterns in a series of observations representing unknown speech by comparing the observations to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, the models comprising finite state machines, having multiple state sequences, the method comprising the steps of:
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a) comparing two or more of the observations, representing unknown speech, in one of the blocks of observations, representing known speech, to a subset comprising one or more of the models, to determine a likelihood of a match to each of the one or more models, by determining which of the state sequences of the respective model is the closest match, and how close is the match; b) repeating step a) for models other than those in the subset; and c) repeating steps a) and b) for a different one of the blocks, and thereby recognizing the unknown speech in terms of the known speech. - View Dependent Claims (12, 13, 14)
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15. A computer implemented method of comparing a series of observations representing unknown speech, to stored models representing known speech, by comparing the observations to stored models, the series of observations being grouped into one or more blocks each comprising two or more of the observations, the models comprising finite state machines, having multiple state sequences, the method comprising, for each of the one or more blocks, the steps of:
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a) comparing two or more of the observations, representing unknown speech, in the respective block, to a subset comprising one or more of the models, representing known speech, to determine a likelihood of a match to each of the one or more models, by determining which of the state sequences of the respective model is the closest match, and how close is the match; and b) repeating step a) for models other than those in the subset, and thereby recognize the unknown speech in terms of the known speech.
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16. Software stored on a computer readable medium for comparing a series of observations representing unknown speech, to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, the software being programmed for carrying out the steps of:
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a) comparing two or more of the observations, representing unknown speech, in one of the blocks of observations, representing known speech, to a subset comprising one or more of the models, to determine a likelihood of a match to each of the one or more models; b) repeating step a) for models other than those in the subset; and c) repeating steps a) and b) for a different one of the blocks, and thereby recognizing the unknown speech in terms of the known speech.
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17. Software stored on a computer readable medium for recognising patterns in a series of observations, representing unknown speech, by comparing the observations to stored models, representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, the models comprising finite state machines, having multiple state sequences, the software being programmed to carry out the steps of:
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a) comparing two or more of the observations, representing unknown speech, in one of the blocks of observations, to a subset comprising one or more of the models, representing known speech, to determine a likelihood of a match to each of the one or more models, by determining which of the state sequences of the respective model is the closest match, and how close is the match; b) repeating step a) for models other than those in the subset; and c) repeating steps a) and b) for a different one of the blocks, and thereby recognizing the unknown speech in terms of the known speech.
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18. Software stored on a computer readable medium for comparing a series of observations representing unknown speech, to stored models representing known speech, by comparing the observations to stored models, the series of observations being grouped into one or more blocks each comprising two or more of the observations, the models comprising finite state machines, having multiple state sequences, the software being programmed to carry out for each of the one or more blocks, the steps of:
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a) comparing two or more of the observations, representing unknown speech, in the respective block, to a subset comprising one or more of the models, representing known speech, to determine a likelihood of a match to each of the one or more models, by determining which of the state sequences of the respective model is the closest match, and how close is the match; and b) repeating step a) for models other than those in the subset, and thereby recognizing the unknown speech in terms of the known speech.
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19. A speech recognition processor for comparing a series of observations representing unknown speech, to stored models representing known speech, the series of observations being divided into at least two blocks each comprising two or more of the observations, the processor comprising:
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a) first means for comparing two or more of the observations, representing unknown speech, in one of the blocks of observations, to a subset comprising one or more of the models, representing known speech, to determine a likelihood of a match to each of the one or more models; and b) second means for comparing the two or more observations to models other than those in the subset; and wherein said first means and said second means iteratively compare the series of observations to the stored models to therebv recognize the unknown speech in terms of the known speech.
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20. A speech recognition processor for recognising patterns in a series of observations by comparing the observations to stored models, the series of observations being divided into at least two blocks each comprising two or more of the observations, the models comprising finite state machines, having multiple state sequences, the processor comprising:
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a) first means for comparing two or more of the observations, representing unknown speech, in one of the blocks of observations, to a subset comprising one or more of the models, representing known speech, to determine a likelihood of a match to each of the one or more models, by determining which of the state sequences of the respective model is the closest match, and how close is the match; and b) second means for comparing the two or more of the observations to models other than those in the subset; wherein said first means and said second means iteratively compare the series of observations to the stored models to thereby recognize the unknown speech in terms of the known speech.
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21. A speech recognition processor for comparing a series of observations representing unknown speech, to stored models representing known speech, by comparing the observations to stored models, the series of observations being grouped into one or more blocks each comprising two or more of the observations, the models comprising finite state machines, having multiple state sequences, the processor comprising:
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a) first means for comparing two or more of the observations, representing unknown speech, in the respective block, to a subset comprising one or more of the models, representing known speech, to determine a likelihood of a match to each of the one or more models, by determining which of the state sequences of the respective model is the closest match, and how close is the match; and b) second means for comparing the two or more of the observations to models other than those in the subset, to thereby recognize the unknown speech in terms of the known speech.
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Specification