公开(公告)号：DE69424196D1

公开(公告)日：2000-06-08

申请号：DE69424196

申请日：1994-01-12

Applicant: IBM

Inventor： BELLEGARDA JEROME RENE ,  NAHAMOO DAVID ,  NATHAN KRISHNA SUNDARAM

IPC: G06K9/46 ,  G06K9/03 ,  G06K9/22 ,  G06K9/62 ,  G06K9/68

Abstract: Methods and apparatus are disclosed for recognizing handwritten characters in response to an input signal from a handwriting transducer. A feature extraction and reduction procedure is disclosed that relies on static or shape information, wherein the temporal order in which points are captured by an electronic tablet may be disregarded. A method of the invention generates and processes the tablet data with three independent sets of feature vectors which encode the shape information of the input character information. These feature vectors include horizontal (x-axis) and vertical (y-axis) slices of a bit-mapped image of the input character data, and an additional feature vector to encode an absolute y-axis displacement from a baseline of the bit-mapped image. It is shown that the recognition errors that result from the spatial or static processing are quite different from those resulting from temporal or dynamic processing. Furthermore, it is shown that these differences complement one another. As a result, a combination of these two sources of feature vector information provides a substantial reduction in an overall recognition error rate. Methods to combine probability scores from dynamic and the static character models are also disclosed.

公开(公告)号：DE69422466D1

公开(公告)日：2000-02-10

申请号：DE69422466

申请日：1994-09-07

Applicant: IBM

Inventor： ELLOZY HAMED A ,  KANEVSKY DIMITRI ,  KIM MICHELLE Y ,  NAHAMOO DAVID ,  PICHENY MICHAEL A ,  ZADROZNY WLODEK W

IPC: G03B31/00 ,  G06F17/30 ,  G10L15/00 ,  G10L15/18 ,  G10L15/22 ,  G10L15/26 ,  G11B27/028 ,  G11B27/10 ,  G11B27/28 ,  H04N5/91

公开(公告)号：DE69224253T2

公开(公告)日：1998-08-13

申请号：DE69224253

申请日：1992-08-31

Applicant: IBM

Inventor： BAHL LALIT R ,  BELLEGARDA JEROME R ,  EPSTEIN EDWARD ADAM ,  LUCASSEN JOHN M ,  NAHAMOO DAVID ,  PICHENY MICHAEL ALAN

IPC: G10L19/00 ,  G10L15/02 ,  G10L19/02 ,  H03M7/30 ,  G10L5/00 ,  G10L5/06 ,  G10L7/08 ,  G10L9/06 ,  G10L9/16

公开(公告)号：SG43733A1

公开(公告)日：1997-11-14

申请号：SG1996000324

申请日：1994-09-08

Applicant: IBM

Inventor： EPSTEIN MARK EDWARD ,  GOPALAKISHNAN PONANI S ,  NAHAMOO DAVID ,  PICHENY MICHAEL ALAN ,  SEDIVY JAN

IPC: G10L15/02 ,  G10L19/00 ,  G10L19/02 ,  H03M7/30 ,  H04B14/04 ,  G10L5/06 ,  G10L3/00 ,  G10L5/00 ,  G10L7/08 ,  G10L9/06 ,  G10L9/18

Abstract: A speech coding apparatus and method uses classification rules to code an utterance while consuming fewer computing resources. The value of at least one feature of an utterance is measured during each of a series of successive time intervals to produce a series of feature vector signals representing the feature values. Classification rules map each feature vector signal from a set of all possible feature vector signals to exactly one of at least two different classes of prototype vector signals. Each class contains a plurality of prototype vector signals. According to the classification rules, a first feature vector signal is mapped to a first class of prototype vector signals. The closeness of the feature value of the first feature vector signal is compared to the parameter values of only the prototype vector signals in the first class of prototype vector signals to obtain prototype match scores for the first feature vector signal and each prototype vector signal in the first class. At least the identification value of at least the prototype vector signal having the best prototype match score is output as a coded utterance representation signal of the first feature vector signal.

公开(公告)号：DE3878071T2

公开(公告)日：1993-08-12

申请号：DE3878071

申请日：1988-05-31

Applicant: IBM

Inventor： NADAS ARTHUR JOSEPH ,  NAHAMOO DAVID

IPC: G10L11/00 ,  G10L15/02 ,  G10L15/06 ,  G10L15/12 ,  G10L15/20 ,  G10L19/00 ,  G10L21/02 ,  G10L5/06

Abstract: In a speech processor system in which prototype vectors of speech are generated by an acoustic processor under reference noise and known ambient conditions and in which feature vectors of speech are generated during varying noise and other ambient and recording conditions, normalized vectors are generated to reflect the form the feature vectors would have if generated under the reference conditions. The normalized vectors are generated by: (a) applying an operator function Aito a set of feature vectors x occurring at or before time interval i to yield a normalized vector yi = Ai(x); (b) determining a distance error vector Ei by which the normalized vector is projectively moved toward the closest prototype vector to the normalized vector yi; (c) up-dating the operator function for next time interval to correspond to the most recently determined distance error vector; and (d) incrementing i to the next time interval and repeating steps (a) through (d) wherein the feature vector corresponding to the incremented i value has the most recent up-dated operator function applied thereto. With successive time intervals, successive normalized vectors are generated based on a successively up-dated operator function. For each normalized vector, the closest prototype thereto is associated therewith. The string of normalized vectors or the string of associated prototypes (or respective label identifiers thereof) or both provide output from the acoustic processor.

公开(公告)号：CA2072721A1

公开(公告)日：1993-04-04

申请号：CA2072721

申请日：1992-06-29

Applicant: IBM

Inventor： BAHL LALIT R ,  BELLEGARDA JEROME R ,  EPSTEIN EDWARD A ,  LUCASSEN JOHN M ,  NAHAMOO DAVID ,  PICHENY MICHAEL A

IPC: G10L19/00 ,  G10L15/02 ,  G10L19/02 ,  H03M7/30

公开(公告)号：CA2068041A1

公开(公告)日：1993-01-17

申请号：CA2068041

申请日：1992-05-05

Applicant: IBM

Inventor： BAHL LALIT R ,  BELLEGARDA JEROME R ,  DE SOUZA PETER V ,  NAHAMOO DAVID ,  PICHENY MICHAEL A

IPC: G10L19/00 ,  G10L15/02 ,  G10L15/06 ,  G10L5/00 ,  G10L5/04 ,  G10L5/06

Abstract: An apparatus for generating a set of acoustic prototype signals for encoding speech includes means for storing a training script model comprises a series of word-segment models. Each word-segment model comprises a series of elementary models. Means are provided for measuring the value of at least one feature of an utterance of the training script during each of a series of time intervals to produce a series of feature vector signals representing the feature values of the utterance. Means are provided for estimating at least one path through the training script model which would produce the entire series of measured feature vector signals. From the estimated path, the elementary model in the training script model which would produce each feature vector signal is estimated. The apparatus further comprises means for clustering the feature vector signals into a plurality of clusters. Each feature vector signal in a cluster corresponds to a single elementary model in a single location in a single word-segment model. Each cluster signal has a cluster value equal to an average of the feature values of all feature vectors in the signal. Finally, the apparatus includes means for storing a plurality of prototype vector signals. Each prototype vector signal corresponds to an elementary model, has an identifier, and comprises at least two partition values. The partition values are equal to combinations of the cluster values of one or more cluster signals corresponding to the elementary model.

公开(公告)号：DE3876379D1

公开(公告)日：1993-01-14

申请号：DE3876379

申请日：1988-09-16

Applicant: IBM

Inventor： PICHENY MICHAEL ALAN ,  NAHAMOO DAVID ,  DE SOUZA PETER VINCENT ,  BROWN PETER FITZHUGH

IPC: G10L11/00 ,  G10L15/02 ,  G10L15/06 ,  G10L15/14 ,  G10L5/06

公开(公告)号：CA2060591A1

公开(公告)日：1992-09-23

申请号：CA2060591

申请日：1992-02-04

Applicant: IBM

Inventor： BAHL LALIT R ,  PICHENY MICHAEL A ,  NAHAMOO DAVID ,  DE SOUZA PETER V

IPC: G10L19/00 ,  G10L15/02 ,  G10L19/02 ,  H03M7/30 ,  G10L9/02 ,  G10L9/14 ,  G10L9/08

Abstract: The present invention is related to speech recognition and particularly to a new type of vector quantizer and a new vector quantization technique in which the error rate of associating a sound with an incoming speech signal is drastically reduced. To achieve this end, the present invention technique groups the feature vectors in a space into different prototypes at least two of which represent a class of sound. Each of the prototypes may in turn have a number of subclasses or partitions. Each of the prototypes and their subclasses may be assigned respective identifying values. To identify an incoming speech feature vector, at least one of the feature values of the incoming feature vector is compared with the different values of the respective prototypes, or the subclasses of the prototypes. The class of sound whose group of prototypes, or at least one of the prototypes, whose combined value most closely matches the value of the feature value of the feature vector is deemed to be the class corresponding to the feature vector. The feature vector is then labeled with the identifier associated with that class.