Method for generating a vector codebook, method and device for compressing data, and distributed speech recognition system
1 Assignment
0 Petitions
Accused Products
Abstract
A method for compressing data, the data being represented by an input vector having Q features, wherein Q is an integer higher than 1, including the steps of 1) providing a vector codebook of sub-sets of indexed Q-feature reference vectors and threshold values associated with the sub-sets for a prefixed feature; 2) identifying a sub-set of reference vectors among the sub-sets by progressively comparing the value of a feature of the input vector which corresponds to the prefixed feature, with the threshold values associated with the sub-sets; and 3) identifying the reference vector which, within the sub-set identified in step 2), provides the lowest distortion with respect to the input vector.
25 Citations
68 Claims
-
1-34. -34. (canceled)
-
35. A method for generating a vector codebook providing low data compression computational effort starting from a vector codebook comprising a set of N reference vectors each comprising Q features, wherein N and Q are positive integers higher than 1, comprising the steps of:
-
a) sorting the set of N reference vectors in ascending or descending order with respect to the values of a prefixed feature of the set of N reference vectors; b) subdividing the set of sorted reference vectors in sub-sets; and c) associating with each of said sub-sets a respective threshold value for the prefixed feature. - View Dependent Claims (36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 60, 61, 62, 63)
-
-
49. A method for compressing data, said data being represented by an input vector having Q features, wherein Q is an integer higher than 1, comprising the steps of:
-
1) providing a vector codebook comprising sub-sets of indexed Q-feature reference vectors and threshold values associated with said sub-sets for a prefixed feature, as generated by a method for generating a vector codebook providing low data compression computational effort starting from a vector codebook comprising a set of N reference vectors each comprising Q features, wherein N and Q are positive integers higher than 1, comprising the steps of; a) sorting the step of N reference vectors in ascending or descending order with respect to the values of a prefixed feature of the set of N reference vectors; b) subdividing the set of sorted reference vectors in sub-sets; and c) associating with each of said sub-sets a respective threshold value for the prefixed feature; 2) identifying a sub-set of reference vectors among said sub-sets by progressively comparing the value of a feature of the input vector, which corresponds to said prefixed feature, with the threshold values associated with said sub-sets; and 3) identifying the reference vector which, within the sub-set identified in step
2) provides the lowest distortion with respect to the input vector. - View Dependent Claims (50, 51, 52, 53, 54, 55, 56, 59)
-
-
57. A device suitable for data compression comprising:
-
a feature extraction unit for processing a digital input data so as to provide Q-feature vectors, wherein Q is an integer higher than 1; a memory unit for storing at least one vector codebook comprising predetermined sub-sets of sorted indexed Q-feature reference vectors and predetermined threshold values associated with said predetermined sub-sets; and a data compression unit for identifying, for each input Q-feature vector provided by the feature extraction unit, one of the predetermined sub-sets by comparing a predetermined feature of the input vector with said predetermined thresholds, and for identifying, within the identified sub-set, the reference vector which provides the lowest distortion with respect to the input feature vector. - View Dependent Claims (58, 64)
-
-
65. A distributed speech recognition system comprising:
-
a user device suitable for data compression comprising; a feature extraction unit for processing a digital input data so as to provide Q-feature vectors, wherein Q is an integer higher than 1; a memory unit for storing at least one vector codebook comprising predetermined sub-sets of sorted indexed Q-feature reference vectors and predetermined threshold values associated with said predetermined sub-sets; and a data compression unit for identifying, for each input Q-feature vector provided by the feature extraction unit, one of the predetermined sub-sets by comparing a predetermined feature of the input vector with said predetermined thresholds, and for identifying, within the identified sub-set, the reference vector which provides the lowest distortion with respect to the input feature vector; a recognition device for reconstructing the digital input data; and a transmission channel for data transmission between the user device and the recognition device. - View Dependent Claims (66, 67, 68)
-
Specification