Matthew W Hartman

US Patent:

20070292835, Dec 20, 2007

Filed:

Jun 6, 2006

Appl. No.:

11/447318

Inventors:

Clement Edwin Hartman - Whittier CA, US
Matthew Ryan Hartman - Whittier CA, US
Geoffrey Dean Hartman - Tarzana CA, US

International Classification:

G09B 3/00

US Classification:

434350

Abstract:

A method for reporting student relevant data to parents that provides secure access by a validated user over a computer network to forms that enable the user to associate student relevant data categories with a particular student. The computer network enables selective display of the forms on a user's terminal. The method enables a user, e.g., teacher or administrator, to select a student and to associate student relevant data categories therewith. The method creates a message for each selected student corresponding to the associated student relevant data categories. The message is transmitted to parents; preferably in their language using prerecorded digital messages. Student relevant data comprises informational and behavioral data. The method preferably enables the user to select a set of students in one step and to concurrently associate student relevant data categories therewith. Messages sent by telephone to a parent are each preferably sent with different caller IDs.

US Patent:

54349478, Jul 18, 1995

Filed:

Feb 23, 1993

Appl. No.:

8/021364

Inventors:

Ira A. Gerson - Schaumburg IL
Mark A. Jasiuk - Chicago IL
Matthew A. Hartman - Schaumburg IL

Assignee:

Motorola - Schaumburg IL

International Classification:

G10L 914

US Classification:

395 228

Abstract:

An Rth-order filter models the frequency response of multiple filters, to provide a filter which offers the control of multiple filters without the complexity of multiple filters. The Rth-order filter can be used as a spectral noise weighting filter or a combination of a short-term predictor filter and a spectral noise weighting filter, referred to as the spectrally noise weighted synthesis filter, depending on which embodiment is employed. In general, the method models the frequency response of L Pth-order filters by a single Rth-order filter, where the order R

US Patent:

55704530, Oct 29, 1996

Filed:

May 4, 1995

Appl. No.:

8/434868

Inventors:

Ira A. Gerson - Schaumburg IL
Mark A. Jasiuk - Chicago IL
Matthew A. Hartman - Schaumburg IL

Assignee:

Motorola, Inc. - Schaumburg IL

International Classification:

G10L 914

US Classification:

395 228

Abstract:

A digital speech coding method uses an Rth-order filter to model the frequency response of multiple filters, thereby, providing a filter which offers the control of multiple filters without the complexity of multiple filters. The Rth-order filter can be used as a spectral noise weighting filter or a combination of a short-term predictor filter and a spectral noise weighting filter, referred to as the spectrally noise weighted synthesis filter, depending on which embodiment is employed. In general, the method models the frequency response of L Pth-order filters by a single Rth-order filter, where the order R

US Patent:

56757026, Oct 7, 1997

Filed:

Mar 8, 1996

Appl. No.:

8/611608

Inventors:

Ira A. Gerson - Schaumburg IL
Mark A. Jasiuk - Chicago IL
Matthew A. Hartman - Schaumburg IL

Assignee:

Motorola, Inc. - Schaumburg IL

International Classification:

G10L 908

US Classification:

395 232

Abstract:

A Vector-Sum Excited Linear Predictive Coding (VSELP) speech coder provides improved quality and reduced complexity over a typical speech coder. VSELP uses a codebook which has a predefined structure such that the computations required for the codebook search process can be significantly reduced. This VSELP speech coder uses single or multi-segment vector quantizer of the reflection coefficients based on a Fixed-Point-Lattice-Technique (FLAT). Additionally, this speech coder uses a pre-quantizer to reduce the vector codebook search complexity and a high-resolution scalar quantizer to reduce the amount of memory needed to store the reflection coefficient vector codebooks. Resulting in a high quality speech coder with reduced computations and storage requirements.

US Patent:

56921012, Nov 25, 1997

Filed:

Nov 20, 1995

Appl. No.:

8/560857

Inventors:

Ira A. Gerson - Schaumburg IL
Mark A. Jasiuk - Chicago IL
Matthew A. Hartman - Bloomington IL

Assignee:

Motorola, Inc. - Schaumburg IL

International Classification:

G10L 914

US Classification:

395 231

Abstract:

An improved speech coder provides a more natural sounding replication of speech by modifying the mean-squared error criterion for the selected speech coder parameters. Specifically, the modification emphasizes the signal components that the speech coder has difficulty matching, i. e. the high frequencies. This emphasis is constrained to certain limitations to avoid over-emphasizing the speech.

US Patent:

58262245, Oct 20, 1998

Filed:

Feb 29, 1996

Appl. No.:

8/609027

Inventors:

Ira A. Gerson - Schaumburg IL
Mark A. Jasiuk - Chicago IL
Matthew A. Hartman - Schaumburg IL

Assignee:

Motorola, Inc. - Schaumburg IL

International Classification:

G10L 914
G10L 908

US Classification:

704222

Abstract:

An input speech signal is encoded as one or more reflection coefficients. To reduce storage requirements, the reflection coefficients are scalar quantized by storing an N-bit code rather than the entire reflection coefficient. An exemplary value for N is 8. A table is provided having 2. sup. N reflection coefficient values. The N-bit code is used to look up reflection coefficient values from the table. To reduce spectral distortion due to scalar quantization, the reflection coefficient values in the table are non-linearly scaled.

US Patent:

56175094, Apr 1, 1997

Filed:

Mar 29, 1995

Appl. No.:

8/413146

Inventors:

William M. Kushner - Arlington Heights IL
Edward Srenger - Schaumburg IL
Matthew A. Hartman - Bloomington IL

Assignee:

Motorola, Inc. - Schaumburg IL

International Classification:

G10L 900

US Classification:

395 265

Abstract:

In a statistical based speech recognition system, one of the key issues is the selection of the Hidden Markov Model that best matches a given sequence of feature observations. The problem is usually addressed by the calculation of the maximum likelihood, ML, state sequence by means of a Viterbi or other decoder. Noise or inadequate training can produce a ML sequence associated with a Hidden Markov Model other than the correct model. The method of the present invention provides improved robustness by combining the standard ML state sequence score (416) with an additional path score (418) derived from the dynamics of the ML score as a function of time. These two scores, when combined, form a hybrid metric (420) that, when used with the decoder, optimizes selection of the correct Hidden Markov Model (422).