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Analysis

1 / 214
1.20180341632Conversation utterance labeling
US - 29.11.2018
Int.Class G06F 17/24
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
17Digital computing or data processing equipment or methods, specially adapted for specific functions
20Handling natural language data
21Text processing
24Editing, e.g. insert/delete
 Appl.No 15603091 Applicant International Business Machines Corporation Inventor Rama Kalyani T. Akkiraju

A method, a computer program product, and an information handling system is provided for labeling unlabeled utterances given a taxonomy of labels utilizing topic word semi-supervised learning.

2.20210182732Data center disaster circuit breaker utilizing machine learning
US - 17.06.2021
Int.Class G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
 Appl.No 16714070 Applicant SAP SE Inventor Yang Peng

Calls received by a data center that are associated with a request are monitored. Features are subsequently extracted from the monitored calls so that a machine learning model may use such features to determine that the request will cause the data center to malfunction. The machine learning model can be trained using data derived from a transaction log for the data center. At least one correction action to prevent the data center from malfunctioning can then be initiated in response to such determination. Related apparatus, systems, techniques and articles are also described.

3.20240395267SYSTEM AND METHOD FOR ENHANCEMENT OF A DEGRADED AUDIO SIGNAL
US - 28.11.2024
Int.Class G10L 19/02
GPHYSICS
10MUSICAL INSTRUMENTS; ACOUSTICS
LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
19Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
02using spectral analysis, e.g. transform vocoders or subband vocoders
 Appl.No 18674555 Applicant Dolby Laboratories Licensing Corporation Inventor Jia Dai

The present disclosure relates to the field of audio enhancement, and in particular to methods, devices and software for supervised training of a machine learning model, MLM, the MLM trained to enhance a degraded audio signal by calculating gains to be applied to frequency bands of the degraded audio signal. The present disclosure further relates to methods, devices and software for use of such a trained MLM.

4.20190373111AUTOMATIC CALL CLASSIFICATION USING MACHINE LEARNING
US - 05.12.2019
Int.Class H04M 3/436
HELECTRICITY
04ELECTRIC COMMUNICATION TECHNIQUE
MTELEPHONIC COMMUNICATION
3Automatic or semi-automatic exchanges
42Systems providing special services or facilities to subscribers
436Arrangements for screening incoming calls
 Appl.No 16366605 Applicant Upcall Inc. Inventor Jason Rute

A system may obtain audio files of phone calls and predict the outcomes of the phone calls using a machine learning model. The system may translate the audio files to text transcripts and convert the text transcripts into vectors. The vectors may be input into a machine learning model trained on prior examples of phone calls and their true outcomes. The machine learning model may output a predicted classification of the outcome of the phone call.

5.20240031477Machine learning dataset generation using a natural language processing technique
US - 25.01.2024
Int.Class H04M 3/24
HELECTRICITY
04ELECTRIC COMMUNICATION TECHNIQUE
MTELEPHONIC COMMUNICATION
3Automatic or semi-automatic exchanges
22Arrangements for supervision, monitoring or testing
24with provision for checking the normal operation
 Appl.No 18212429 Applicant Capital One Services, LLC Inventor Jeffrey Rule

A server can receive a plurality of records at a databases such that each record is associated with a phone call and includes at least one request generated based on a transcript of the phone call. The server can generate a training dataset based on the plurality of records. The server can further train a binary classification model using the training dataset. Next, the server can receive a live transcript of a phone call in progress. The server can generate at least one live request based on the live transcript using a natural language processing module of the server. The server can provide the at least one live request to the binary classification model as input to generate a prediction. Lastly, the server can transmit the prediction to an entity receiving the phone call in progress. The prediction can cause a transfer of the call to a chatbot.

6.10229370System and method for managing routing of customer calls to agents
US - 12.03.2019
Int.Class H04M 3/51
HELECTRICITY
04ELECTRIC COMMUNICATION TECHNIQUE
MTELEPHONIC COMMUNICATION
3Automatic or semi-automatic exchanges
42Systems providing special services or facilities to subscribers
50Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers
51Centralised call answering arrangements requiring operator intervention
 Appl.No 16110872 Applicant MASSACHUSETTS MUTUAL LIFE INSURANCE COMPANY Inventor Sears Merritt

A call management system of a call center retrieves customer demographic data associated with a customer identifier for an inbound caller, i.e., customer. A predictive model including a logistic regression model and tree based model determines a value prediction signal for the identified customer. Based on the value prediction signal determined, the predictive model classifies the identified customer into a first value group or a second value group. The call management system routes a customer classified in the first value group to a first call queue for connection to one of a first pool of call center agents who are authorized to present an offer to purchase a product, and routes a customer classified in the second value group to a second call queue for connection to one of a second pool of call center agents who are not authorized to present the offer to purchase the product.

7.20210168237Machine learning dataset generation using a natural language processing technique
US - 03.06.2021
Int.Class H04M 3/24
HELECTRICITY
04ELECTRIC COMMUNICATION TECHNIQUE
MTELEPHONIC COMMUNICATION
3Automatic or semi-automatic exchanges
22Arrangements for supervision, monitoring or testing
24with provision for checking the normal operation
 Appl.No 17170329 Applicant Capital One Services, LLC Inventor Jeffrey Rule

A server can receive a plurality of records at a databases such that each record is associated with a phone call and includes at least one request generated based on a transcript of the phone call. The server can generate a training dataset based on the plurality of records. The server can further train a binary classification model using the training dataset. Next, the server can receive a live transcript of a phone call in progress. The server can generate at least one live request based on the live transcript using a natural language processing module of the server. The server can provide the at least one live request to the binary classification model as input to generate a prediction. Lastly, the server can transmit the prediction to an entity receiving the phone call in progress. The prediction can cause a transfer of the call to a chatbot.

8.20210092224MACHINE LEARNING DATASET GENERATION USING A NATURAL LANGUAGE PROCESSING TECHNIQUE
US - 25.03.2021
Int.Class H04M 3/24
HELECTRICITY
04ELECTRIC COMMUNICATION TECHNIQUE
MTELEPHONIC COMMUNICATION
3Automatic or semi-automatic exchanges
22Arrangements for supervision, monitoring or testing
24with provision for checking the normal operation
 Appl.No 16579340 Applicant Capital One Services, LLC Inventor Jeffrey RULE

A server can receive a plurality of records at a databases such that each record is associated with a phone call and includes at least one request generated based on a transcript of the phone call. The server can generate a training dataset based on the plurality of records. The server can further train a binary classification model using the training dataset. Next, the server can receive a live transcript of a phone call in progress. The server can generate at least one live request based on the live transcript using a natural language processing module of the server. The server can provide the at least one live request to the binary classification model as input to generate a prediction. Lastly, the server can transmit the prediction to an entity receiving the phone call in progress. The prediction can cause a transfer of the call to a chatbot.

9.20190392854Doppler microphone processing for conference calls
US - 26.12.2019
Int.Class G10L 21/0208
GPHYSICS
10MUSICAL INSTRUMENTS; ACOUSTICS
LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
21Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
02Speech enhancement, e.g. noise reduction or echo cancellation
0208Noise filtering
 Appl.No 16361403 Applicant Capital One Services, LLC Inventor David Kelly Wurmfeld

Systems and methods are provided for conducting conference calls using doppler-based, i.e., reverberation-based techniques. The embodiments comprise a call device performing operations to join a call session hosted on a session server; receive sensor data comprising an audio signal from a first microphone and location information associated with the first microphone; determine a reverberation parameter associated with the location information; generate a first processed audio signal based on the audio signal and the reverberation parameter; and transmit the first processed audio signal to the session server. The session server may perform operations to receive a respective processed audio signal; determine a sound quality parameter of the respective processed audio signal; generate a balanced audio signal based on the sound quality parameter and the received processed audio signal; and transmit the balanced audio signal to a remote call device belonging to a second party.

10.WO/2024/096828A SUGGESTION SYSTEM
WO - 10.05.2024
Int.Class G06F 16/54
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
16Information retrieval; Database structures therefor; File system structures therefor
50of still image data
54Browsing; Visualisation therefor
 Appl.No PCT/TR2023/050363 Applicant TURKIYE GARANTI BANKASI ANONIM SIRKETI Inventor TASAR, Davut Emre
The present invention relates to a system (1) which enables to suggest an appropriate product to persons in accordance with the input data received from persons by analysing the text, image, audio or motion input data –that are received over a chatbot or metaverse included on an application (3) by means of electronic devices or wearable technology devices of the persons– by machine learning analysis and processing methods such as natural language understanding and processing, digital image processing, signal processing, tabular data processing, graph artificial neural networks; and to provide a sustainable communication between the person and the chatbot by recording all inputs received and suggestion results generated, in a database (4) and blockchain network (5).
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