# US 2017/0286393 A1 · Common phrase identification and language dictation recognition systems and methods for using the same

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- Number: US 2017/0286393 A1
- Document ID: US20170286393A1
- Status: Published application
- Kind: A1
- Application number: 15/624,411
- Filed: 2017-06-15
- Published: 2017-10-05
- Earliest claimed: 2010-10-05
- Assignees: Infraware Inc.
- Applicants: InfraWare, Inc.
- Inventors: Nathan Lindle; Nick Mahurin
- Web page: https://patentgrep.com/patent/US20170286393A1

## CPC

- G10L 15/26: Speech to text systems (G10L15/08 takes precedence)
- G01L 15/00: Devices or apparatus for measuring two or more fluid pressure values simultaneously
- G06F 40/149: Adaptation of the text data for streaming purposes, e.g. Efficient XML Interchange [EXI] format
- G06F 40/205: Parsing
- G10L 15/00: Speech recognition (G10L17/00 takes precedence)
- G10L 15/02: Feature extraction for speech recognition; Selection of recognition unit
- G10L 15/1822: {Parsing for meaning understanding}
- G10L 15/183: using context dependencies, e.g. language models
- G10L 15/30: Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
- G10L 2015/025: {Phonemes, fenemes or fenones being the recognition units}
- G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G01L: MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE (weighing G01G)
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

In at least one exemplary embodiment for common phrase identification and language dictation recognition systems and methods for using the same, the system comprises a database capable of receiving a plurality of verbal records, the verbal record comprising at least one identifier and at least one verbal feature and a processor operably coupled to the database, where the processor has and executes a software program. The processor being operational to identify a subset of the plurality of verbal records from the database, extract at least one verbal feature from the identified records, analyze the at least one verbal feature of the subset of the plurality of verbal records, process the subset of the plurality of records using the analyzed feature according to at least one reasoning approach, generate a processed verbal record using the processed subset of the plurality of records, and deliver the processed verbal record to a recipient. The processor being further operational to identify common phrases in parts of the verbal record, identifying a body of work for building a set of common phrases, analyze documents in a training set to find some common phrases, and replacing phrases with the common phrases.

## Claims

### Claim 1

A computerized method for analyzing verbal records to improve a textual transcript, the method comprising the steps of:
identifying a training set and a test set of transcribed verbal records, the training set comprising a first subset of a plurality of transcribed verbal records, and the test set comprising a different second subset of the plurality of transcribed verbal records;
for the each verbal record in the training set, determine a plurality of possible common phrases;
for each of the plurality of possible common phrases, determine a best parameter;
saving the best parameter for the each of the plurality of possible common phrases; and,
applying the each of the plurality of possible common phrases to the verbal records to create the textual transcript.

### Claim 2 (depends on 1)

The method of claim 1, wherein the step of determining a plurality of possible common phrases further comprises finding a plurality of sequences of words appearing in the each verbal record in the training set.

### Claim 3 (depends on 2)

The method of claim 2, wherein the sequences of words is at least five words long.

### Claim 4 (depends on 1)

The method of claim 1, wherein the step of determining a plurality of possible common phrases further comprises finding alternative phrases for each of the plurality of possible common phrases.

### Claim 5 (depends on 4)

The method of claim 4, wherein finding alternative phrases further comprises comparing a first possible common phrases, and a second possible common phrase to determine if there is overlap there between.

### Claim 6 (depends on 1)

The method of claim 1, wherein the step of determining a plurality of possible common phrases further comprises finding an accuracy for each of the plurality of possible common phrases.

### Claim 7 (depends on 6)

The method of claim 6, wherein finding an accuracy for each of the plurality of possible common phrases comprises finding a soft match for each of the plurality of common phrases.

### Claim 8 (depends on 7)

The method of claim 7, wherein finding a soft match further comprises testing out each of the plurality of common phrases against each of the transcribed verbal records in the training set.

### Claim 9 (depends on 1)

The method of claim 1, wherein determining a best parameter comprises:
selecting a plurality of trial parameters, the plurality of trial parameters selected from a group consisting of maximum words, minimum percentage, and false positive rate;
modifying the each of the transcribed verbal records in the test set using the each of the plurality of common phrases;
calculating the performance of the each of the plurality of common phrases based on the each of the plurality of trial parameters; and
selecting a best parameter, the best parameter being the trial parameter with the best performance.

### Claim 10 (depends on 9)

The method of claim 9, wherein calculating the performance comprises finding the number transcription errors in the each of the transcribed verbal records in the test set.

### Claim 11 (depends on 1)

The method of claim 1, wherein saving the best parameter comprises saving the each of the plurality of common phrases with the corresponding best parameter.

### Claim 12 (depends on 1)

The method of claim 1, wherein creating the textual transcript comprises:
selecting a plurality of verbal records from a database, wherein each verbal record in the plurality of verbal records comprises a combination of at least one identifier, at least one text feature, and at least one phonetic feature;
identifying a subset of the plurality of verbal records from the database;
modifying the identified subset of the plurality of verbal records to create a modified verbal record, wherein the system uses the at least one analyzed phonetic feature, the at least one text feature, and the each of the plurality of common phrases with the corresponding best parameter, or a combination thereof, to generate the modified verbal record; and
delivering the modified verbal record to a recipient.

### Claim 13

A system for analyzing verbal records to improve a textual transcript, the system comprising:
a database configured to receive a plurality of transcribed verbal records;
a processor operably connected to the database, and configured to:
identify a training set and a test set of the transcribed verbal records, the training set comprising a first subset of the plurality of transcribed verbal records, and the test set comprising a different second subset of the plurality of transcribed verbal records;
determine a plurality of possible common phrases for the each verbal record in the training set;
determine a best parameter for each of the plurality of possible common phrases;
save the best parameter for the each of the plurality of possible common phrases; and,
apply the each of the plurality of possible common phrases to the verbal records to create the textual transcript.

### Claim 14 (depends on 13)

The system of claim 13, wherein the processor is further configured to find a plurality of sequences of words appearing in the each verbal record in the training set.

### Claim 15 (depends on 14)

The system of claim 14, wherein the sequences of words is at least five words long.

### Claim 16 (depends on 13)

The system of claim 13, wherein the processor is further configured to find alternative phrases for each of the plurality of possible common phrases.

### Claim 17 (depends on 16)

The system of claim 16, wherein the processor is further configured to compare a first possible common phrases, and a second possible common phrase to determine if there is overlap there between.

### Claim 18 (depends on 13)

The system of claim 13, wherein the processor is further configured to find an accuracy for each of the plurality of possible common phrases.

### Claim 19 (depends on 18)

The system of claim 18, wherein the processor is further configured to find a soft match for each of the plurality of common phrases.

### Claim 20 (depends on 19)

The system of claim 19, wherein the processor is further configured to test out each of the plurality of common phrases against each of the transcribed verbal records in the training set.

### Claim 21 (depends on 13)

The system of claim 13, wherein the processor is further configured to:
select a plurality of trial parameters, the plurality of trial parameters selected from a group consisting of maximum words, minimum percentage, and false positive rate;
modify the each of the transcribed verbal records in the test set using the each of the plurality of common phrases;
calculate the performance of the each of the plurality of common phrases based on the each of the plurality of trial parameters; and
select a best parameter, the best parameter being the trial parameter with the best performance.

### Claim 22 (depends on 21)

The system of claim 21, wherein the processor is further configured to find the number transcription errors in the each of the transcribed verbal records in the test set.

### Claim 23 (depends on 13)

The system of claim 13, wherein the processor is further configured to save the each of the plurality of common phrases with the corresponding best parameter.

### Claim 24 (depends on 13)

The system of claim 13, wherein the processor is further configured to:
select a plurality of verbal records from a database, wherein each verbal record in the plurality of verbal records comprises a combination of at least one identifier, at least one text feature, and at least one phonetic feature;
identify a subset of the plurality of verbal records from the database;
modify the identified subset of the plurality of verbal records to create a modified verbal record, wherein the system uses the at least one analyzed phonetic feature, the at least one text feature, and the each of the plurality of common phrases with the corresponding best parameter, or a combination thereof, to generate the modified verbal record; and
deliver the modified verbal record to a recipient.