Abstract: Systems and methods enrich speech to text communications between users in speech chat sessions using a speech emotion recognition model to convert observed emotions in speech samples to enrich text with visual emotion content. The method may include generating a data set of speech samples with labels of a plurality of emotion classes, selecting a set of acoustic features from each of the emotion classes, generating a machine learning (ML) model based on the acoustic features and data set, applying the set of rules based on the selected set of acoustic features and data set, computing a number of rules that have been satisfied, and presenting the enriched text in speech-to-text communications between users in the chat session for visual notice of an observed emotion in the speech sample.

Abstract: A method for training vibrotactile speech perception in the absence of auditory speech includes selecting a first word, generating a first control signal configured to cause at least one vibrotactile transducer to vibrate against a person's body with a first vibration pattern based on the first word, sampling a second word spoken by the person, generating a second control signal configured to cause at least one vibrotactile transducer to vibrate against the person's body with a second vibration pattern based on the sampled second word, and presenting a comparison between the first word and the second word to the person. An array of vibrotactile transducers can be in contact with the person's body.

Abstract: Methods, systems, and computer-readable media for voice-activated selective memory for voice-capturing devices are disclosed. A first voice input from a voice-capturing device is received, via a network, at a service provider environment comprising one or more services. The first voice input comprises one or more utterances from a user of the voice-capturing device. A representation of the first voice input is stored. A second voice input from the voice-capturing device is received, via the network, at the service provider environment. The second voice input represents a command to disregard the first voice input. Based on the second voice input, the representation of the first voice input is deleted.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. In accordance with one example, a method includes, at an electronic device with one or more processors and memory, receiving a first natural-language speech input indicative of a request for media, where the first natural-language speech input comprises a first search parameter; providing, by a digital assistant, a first media item identified based on the first search parameter. The method further includes, while providing the first media item, receiving a second natural-language speech input and determining whether the second input corresponds to a user intent of refining the request for media. The method further includes, in accordance with a determination that the second speech input corresponds to a user intent of refining the request for media: identifying, based on the first parameter and the second speech input, a second media item and providing the second media item.

Abstract: A method for decaying speech processing includes receiving, at a voice-enabled device, an indication of a microphone trigger event indicating a possible interaction with the device through speech where the device has a microphone that, when open, is configured to capture speech for speech recognition. In response to receiving the indication of the microphone trigger event, the method also includes instructing the microphone to open or remain open for a duration window to capture an audio stream in an environment of the device and providing the audio stream captured by the open microphone to a speech recognition system. During the duration window, the method further includes decaying a level of the speech recognition processing based on a function of the duration window and instructing the speech recognition system to use the decayed level of speech recognition processing over the audio stream captured by the open microphone.

Abstract: Technologies are provided for generation of recommendation results using a verbal query. In one embodiment, query data can be generated using a searchable query corresponding to the verbal query. The query data can define a query browse node and a product brand, for example. First product identifiers that match the searchable query can be determined using multiple data repositories. Duplicates from the first product identifiers can be removed, resulting in second product identifiers. Attribute data also can be generated using the second product identifiers. The attribute data can define features for a product identifier. Further, third product identifiers can be determined by applying a filtering model to the second product identifiers. A ranking of the third product identifiers can be generated using an optimization function based on the query data and the product attribute data. A product corresponding to one of the ranked product identifiers represents a recommendation result.

Abstract: The subject matter of this specification can be embodied in, among other things, a method that includes receiving two or more data sets each representing speech of a corresponding individual attending an internet-based social networking video conference session, decoding the received data sets to produce corresponding text for each individual attending the internet-based social networking video conference, and detecting characteristics of the session from a coalesced transcript produced from the decoded text of the attending individuals for providing context to the internet-based social networking video conference session.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speaker diarization are disclosed. In one aspect, a method includes the actions of receiving audio data corresponding to an utterance. The actions further include determining that the audio data includes an utterance of a predefined hotword spoken by a first speaker. The actions further include identifying a first portion of the audio data that includes speech from the first speaker. The actions further include identifying a second portion of the audio data that includes speech from a second, different speaker. The actions further include transmitting the first portion of the audio data that includes speech from the first speaker and suppressing transmission of the second portion of the audio data that includes speech from the second, different speaker.

Abstract: An information processing method includes receiving first text information, which is generated according to a speech, input through a first input device; receiving audio information recorded by a second input device, wherein the audio information is generated and recorded according to the speech; performing speech recognition on the audio information to obtain second text information; and presenting the first text information and the second text information. A correspondence relationship exists between content in the first text information and content in the second text information.

Abstract: A smart device input method based on facial vibration includes: collecting a facial vibration signal generated when a user performs voice input; extracting a Mel-frequency cepstral coefficient from the facial vibration signal; and taking the Mel-frequency cepstral coefficient as an observation sequence to obtain text input corresponding to the facial vibration signal by using a trained hidden Markov model. The facial vibration signal is collected by a vibration sensor arranged on glasses. The vibration signal is processed by: amplifying the collected facial vibration signal; transmitting the amplified facial vibration signal to the smart device via a wireless module; and intercepting a section from the received facial vibration signal as an effective portion and extracting the Mel-frequency cepstral coefficient from the effective portion by the smart device.

Abstract: A system, device and method for enforcing privacy during a communication session with a voice assistant are disclosed. Periodically during the communication session with the voice assistant, sensor data is acquired. The sensor data is processed to determine a number of persons present in an environment of the voice assistant. The communication of private data by the voice assistant is enabled when one person is in the environment and that person is the authorized user. The communication of private data by the voice assistant is disabled when one person is in the environment and that person is not the authorized user. When more than one person is present in the environment of the voice assistant, the communication of private data by the voice assistant may be enabled when the environment of the voice assistant is determined to match the one or more predetermined privacy criteria for a multi-person environment.

Abstract: Machine classifiers in accordance with embodiments of the invention capture long-term temporal dependencies in particular tasks, such as turn-based dialogues. Machine classifiers may be used to help users to perform tasks indicated by the user. When a user utterance is received, natural language processing techniques may be used to understand the user's intent. Templates may be determined based on the user's intent in the generation of responses to solicit information from the user. A variety of persona attributes may be determined for a user. The persona attributes may be determined based on the user's utterances and/or provided as metadata included with the user's utterances. A response persona may be used to generate responses to the user's utterances such that the generated responses match a tone appropriate to the task. A response persona may be used to generate templates to solicit additional information and/or generate responses appropriate to the task.

Abstract: Embodiments of the present application provide a text output method and system, a storage medium, and an electronic device. The system includes at least an automatic speech recognition ASR model group, a text alignment model, and a re-scoring model that are sequentially connected, where the ASR model group includes a plurality of ASR models each configured to convert input audio data into respective first texts; the text alignment model is configured to perform alignment for a plurality of first texts, to obtain a plurality of target texts, where lengths of the plurality of target texts are all equal; and the re-scoring model is configured to score words/terms at each alignment position of the plurality of target texts, to obtain a word/term with the highest score at each alignment position, as a target word/term, and determine the target word/terms, as an output text, by the respective alignment positions.

Abstract: Methods, systems and computer program products for automated testing of dialog systems are provided herein. A computer-implemented method includes receiving information pertaining to a given conversation workspace of an automated dialog system and identifying test case inputs to the automated dialog system, the test case inputs comprising user input for the given conversation workspace that has portions thereof modified and which the automated dialog system maps to a different intent and/or a different entity relative to the user input. The method further includes generating human-interpretable explanations of mappings of portions of the test case inputs to the different intent and/or entity, generating suggestions for modifying intents, entities and dialog flows of the given conversation workspace such that the test case inputs map to the same intent and/or the same entity as their corresponding user input, and outputting the suggestions and the human-interpretable explanations to a user.

Abstract: A computer system identifies and prioritizes issues in electronic documents from electronic social media sources and/or from traditional media sources. The computer system includes a communication network linked to one or more of the sources and a computer server in communication with the communication network. The computer server is configured to receive electronic documents from the sources via the communication network. The computer server has memory and a processor, the memory including processor executable instructions stored in the memory and executable by the processor. The instructions comprise data collection instructions, topic modeling instructions including instructions for weighing and instructions for indicating a distribution for identified issues within each of the retrieved documents, issue assignment instructions, instructions for determining, and instructions for ranking.

Abstract: An ensemble of machine learning models used for real-time prediction of text for an electronic chat with an expert user. A global machine learning model, e.g., a transformer model, trained with domain specific knowledge makes a domain specific generalized prediction. Another machine learning model, e.g., an n-gram model, learns the specific style of the expert user as the expert user types to generate more natural, more expert user specific text. If specific words cannot be predicted with a desired probability level, another word level machine learning model, e.g., a word completion model, completes the words as the characters are being typed. The ensemble therefore produces real-time, natural, and accurate text that is provided to the expert user. Continuous feedback of the acceptance/rejection of predictions by the expert is used to fine tune one or more machine learning models of the ensemble in real time.

Abstract: A video is received. One or more subtitles are determined for the video. Whether a word found in a background of the video is similar to a word found in the one or more subtitles is determined. Responsive to determining the word found in the background of the video is similar to the word found in the one or more subtitles, one or more updated subtitles are generated. The one or more updated subtitles include the word found in the background of the video and remove the word found in the one or more subtitles that is similar. A metric for the one or more updated subtitles is calculated. Whether the metric is larger than a threshold is determined. Responsive to determining the metric is larger than the threshold, the video is updated to include the one or more updated subtitles.

Abstract: A method of electronically documenting a conversation is provided. The method includes capturing audio of a conversation between a first speaker and a second speaker; generating conversation audio data from the captured audio; and segmenting the conversation audio data into a plurality of utterances according to a speaker segmentation technique. The method further includes, for each utterance: storing time data indicating the chronological position of the utterance in the conversation; passing the utterance to a neural network model, the neural network model configured to receive the utterance as an input and generate a feature representation of the utterance as an output; assigning the utterance feature representation to a first speaker cluster or a second speaker cluster according to a clustering technique; assigning a speaker identifier to the utterance based on the cluster assignment of the utterance; and generating a text representation of the utterance.

Abstract: A computer-implemented system and method for vocal training. A user's voice is measured and assessed. Personalized attributes about the user are also acquired including goals of the user. Based on measured aspects of a user's voice, and attributes acquired about the user (based on a combination of user-reported data, mechanically-assessed and/or artificial-intelligence-determined analysis), (1) a report is generated about the user's vocal quality and ability, and (2) the user is given individualized feedback, lessons, and vocal exercises specific to the user's voice, vocal ability, voice-comfort-zone boundaries, and the user's goals in a scientific manner in the form of a virtual-vocal coach. The techniques and goals may be given to the user in real time, and/or used to generate new exercises and drills. By constantly measuring and scoring a user's progress, an ongoing-overall-voice strategy is generated to help the user meet the user's ongoing vocal-development goals.

Abstract: A hearing aid system for individual identification of a hearing aid system may include a wearable camera, a microphone, and at least one processor. The processor may be programmed to receive a plurality of images captured by the wearable camera; receive audio signals representative of sounds captured by the microphone; and identify a first audio signal, from among the received audio signals, representative of a voice of a first individual. The processor may transcribe and store, in a memory, text corresponding to speech associated with the voice of the first individual and determine whether the first individual is a recognized individual. If the first individual is a recognized individual, the processor may associate an identifier of the first recognized individual with the stored text corresponding to the speech associated with the voice of the first individual.

Abstract: Disclosed of the present application is relation to deep learning based voice data processing. The voice data to be detected is converted into target text data based on a voice recognition model so that the keyword text corresponding to the predetermined target voice keyword can be converted. Then, the data is matched with the target text data to determine whether the voice data to be detected includes the target voice keyword based on the matching result. Thus, because the voice recognition model is obtained by deep learning based on the obtained voice recognition data training set, it can obtain high-precision target text data, thereby improving the accuracy of subsequent matching. The problem of low accuracy of detecting voice data for keyword detection can therefor be solved.

Abstract: A pervasive advisor for major purchases and other expenditures may detect that a customer is contemplating a major purchase (e.g., through active listening). The advisor may assist the customer with the timing and manner of making the purchase in a way that is financially sensible in view of the customer's financial situation. A customer may be provided with dynamically-updated information in response to recent actions that may affect an approved loan amount and/or interest rate. Underwriting of a loan may be triggered based on the geo-location of the user. Financial advice may be provided to customers to help them meet their goals using information obtained from third party sources, such as purchase options based on particular goals. The pervasive advisor may thus intervene to assist with budgeting, financing, and timing of major expenditures based on the customer's location and on the customer's unique and changing circumstances.

Abstract: An information processing apparatus 10 includes an acceptance unit 12, a formal language generation unit 14, an inference unit 16, and an update unit 18. The formal language generation unit 14 generates training expressions in a formal language based on parameters prepared in advance and pieces of text accepted by the acceptance unit 12. The inference unit 16 executes at least one inference out of deductive inference and abduction on the above training expressions using a knowledge base prepared in advance. The update unit 18 compares an inference result of the inference unit 16 with a model answer input in advance, and updates parameters such that an inference result that matches the model answer is likely to be obtained through inference performed by the inference unit 16.

Abstract: Systems, methods, and computer-readable media are disclosed for language-agnostic subtitle drift detection and correction. A method may include determining subtitles and/or captions from media content (e.g., videos), the subtitles and/or captions corresponding to dialog in the media content. The subtitles may be broken up into segments which may be analyzed to determine a likelihood of drift (e.g., a likelihood that the subtitles are out of synchronization with the dialog in the media content) for each segment. For segments with a high likelihood of drift, the subtitles may be incrementally adjusted to determine an adjustment that eliminates and/or reduces the amount of drift and the drift in the segment may be corrected based on the drift amount detected. A linear regression model and/or human blocks determined by human operators may be used to otherwise optimize drift correction.

Abstract: A pattern recognition apparatus includes: a model storage part that stores a model(s) generated by using transfer path information indicating a difference of transfer paths of a signal(s) for training, additional to the signal(s) for training, and a pattern recognition part that inputs an input signal and transfer path information indicating a difference of transfer paths of the input signal, and performs pattern recognition of the input signal by using the model(s).

Abstract: Disclosed are systems, methods, and non-transitory computer-readable medium for data input with multi-format validation. The method may include receiving data input via a microphone mounted on a user device and receiving the data input via a camera mounted on the user device. Additionally, the method may include comparing the data input via the microphone and the data input via the camera and determining whether the comparison of the data input exceeds a predetermined confidence level. Additionally, the method may include storing the data input, upon determining that the comparison of the data input exceeds the predetermined confidence level and presenting to the user a notification of validation upon determining that the comparison of the data input does not exceed the predetermined confidence level. Additionally, the method may include receiving from the user a validation of the data input based on the notification of validation and storing the data input based on the validation of the data input.

Abstract: A method and apparatus for automatically generating a meeting summary is disclosed herein. Meeting audio is recorded and converted into a text-based transcript. Handwritten meeting notes are converted into notes text. The transcript and notes text are correlated to provide correlated meeting text. Meeting topics are determined from the correlated meeting text. A meeting summary is generated from the meeting topics.

Abstract: A transcription of audio speech included in electronic content associated with a meeting is created by an ASR model trained on speech-to-text data. The transcription is post-processed by modifying text included in the transcription, for example, by modifying punctuation, grammar, or formatting introduced by the ASR model and by changing or omitting one or more words that were included in both the audio speech and the transcription. After the transcription is post-processed, output based on the post-processed transcription is generated in the form of a meeting summary and/or template.

Abstract: A student neural network may be trained by a computer-implemented method, including: selecting a teacher neural network among a plurality of teacher neural networks, inputting an input data to the selected teacher neural network to obtain a soft label output generated by the selected teacher neural network, and training a student neural network with at least the input data and the soft label output from the selected teacher neural network.

Abstract: A method and system for providing integrated augmented reality (AR) images and content to multiple vehicle occupants having AR devices and methods of generating user-based AR expressions including content control of user generated content.

Abstract: A system and method for use with an assisted user's communication device that includes a display. The method includes providing a user communication device including a processor that is programmed to perform the step of, upon disconnection of an emergency call to a hearing user in which a captioning service has provided text transcription of voice messages from the hearing user, maintaining a link to the captioning service for a predetermined period of time. The processor also is programmed to perform the step of recognizing the call as an emergency call upon placement of the call, and the captioning service is automatically initiated upon the processor performing that recognition.

Abstract: A method, performed by the electronic device, of providing a voice recognition service includes obtaining a user call keyword for activating the voice recognition service, based on a first user voice input; generating a user-customized voice database (DB) by inputting the obtained user-customized keyword to a text to speech module; and obtaining a user-customized feature by inputting an audio signal of the user-customized voice DB to a pre-trained wake-up recognition module.

Abstract: An example device includes a memory configured to store at least one program; a microphone configured to receive a voice; and at least one processor configured to execute the at least one program to control the device to perform operations for sending money to a recipient. The operations include determining a payment intention of a user based on analyzing the received voice input; retrieving contact information from a stored contact list based on the name of the recipient; transmitting the name and the contact information of the recipient to a bank server together with an amount of money specified in the voice input; receiving remittance details from the bank server; and approving the remittance details. The device may analyze the received voice input by using an artificial intelligence (AI) algorithm.

Abstract: A method, computer program product, and computing system for visual diarization of an encounter is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is processed to: associate a first portion of the encounter information with a first encounter participant, and associate at least a second portion of the encounter information with at least a second encounter participant. A visual representation of the encounter information is rendered. A first visual representation of the first portion of the encounter information is rendered that is temporally-aligned with the visual representation of the encounter information. At least a second visual representation of the at least a second portion of the encounter information is rendered that is temporally-aligned with the visual representation of the encounter information.

Abstract: Systems and methods are described for determining whether to activate a voice activated device based on a speaking cadence of the user. When the user speaks with a first cadence the system may determine that the user does not intend to activate the device and may accordingly not to trigger a voice activated device. When the user speaks with a second cadence the system may determine that the user does wish to trigger the device and may accordingly trigger the voice activated device.

Abstract: Devices and techniques are generally described for generating and evaluating utterances. In some examples, an utterance generation and evaluation system can receive intent data and target data. The utterance generation and evaluation system can determine related target names and related intent names and, based on the related target names and related intent names, can generate an utterance phrase. The utterance generation and evaluation system can determine a confidence score associated with the utterance phrase and, based on the confidence score, determine the utterance phrase as a recommended utterance phrase.

Abstract: A technique for semantic search and retrieval that is event-based, wherein is event is composed of a sequence of observations that are user speech or physical actions. Using a first set of conversations, a machine learning model is trained against groupings of utterances therein to generate a speech act classifier. Observation sequences therein are organized into groupings of events and configured for subsequent event recognition. A set of second (unannotated) conversations are then received. The set of second conversations is evaluated using the speech act classifier and information retrieved from the event recognition to generate event-level metadata that comprises, for each utterance or physical action within an event, one or more associated tags. In response to a query, a search is performed against the metadata. Because the metadata is derived from event recognition, the search is performed against events learned from the set of first conversations.

Abstract: Speech fluency evaluation and feedback tools are described. A computing device such as a smartphone may be used to collect speech (and/or other data). The collected data may be analyzed to detect various speech events (e.g., stuttering) and feedback may be generated and provided based on the detected speech events. The collected data may be used to generate a fluency score or other performance metric associated with speech. Collected data may be provided to a practitioner such as a speech therapist or physician for improved analysis and/or treatment.

Abstract: A method may include obtaining first audio data originating at a first device during a communication session between the first device and a second device. The method may also include obtaining a first text string that is a transcription of the first audio data, where the first text string may be generated using automatic speech recognition technology using the first audio data. The method may also include obtaining a second text string that is a transcription of second audio data, where the second audio data may include a revoicing of the first audio data by a captioning assistant and the second text string may be generated by the automatic speech recognition technology using the second audio data. The method may further include generating an output text string from the first text string and the second text string and using the output text string as a transcription of the speech.

Abstract: The disclosure relates an electronic apparatus. The electronic apparatus comprises a voice receiver configured to receive a voice of a speaker; and a processor configured to perform a predetermined operation, obtain a recognition result by applying a voice recognition process to the voice received in the voice receiver during the operation, and perform control based on a standard recognition result previously defined corresponding to at least one pseudo recognition result, based on the obtained recognition result matching the pseudo recognition result previously defined corresponding to the operation.

Abstract: The exemplary embodiments disclose a system and method, a computer program product, and a computer system for resolving the intents of user expression. The exemplary embodiments may include receiving a user expression, receiving a first resolver having an input class and an output class based on the user expression, determining whether the first resolver can be resolved based on the user expression, and based on determining that the first resolver can be resolved based on the user expression, resolving the first resolver.

Abstract: Systems and methods for emotionally intelligent automated chatting are provided. The systems and method provide emotionally intelligent automated (or artificial intelligence) chatting by determining a context and an emotion of a conversation with a user. Based on these determinations, the systems and methods may select one or more responses from a database of responses to a reply to a user query. Further, the systems and methods are able update or train based on user feedback and/or world feedback.

Abstract: Embodiments of the present disclosure are directed to systems and methods for improving functional hearing. In one aspect, the system may include a housing configured to fit within an ear of a user. The housing may include a speaker, an amplifier, a transmitter, and a power supply. Additionally, the housing may include a memory storing instructions and at least one processor configured to execute instructions. The instructions may include receiving an audio input and amplifying the audio input. The instructions may include outputting the amplified audio input from a speaker. The instructions may include converting the audio input into a visual representation of the audio input and transmitting the visual representation to at least one display.

Abstract: A communication system and method usable to facilitate communication between a hearing user and an assisted user. In particular, the system employs a wireless portable tablet or other portable electronic computing device linked to a captioning enabled phone as a remote interface for that phone, thereby providing an assisted user with more options, more freedom, and improved usability of the system.

Abstract: Systems (100) and methods (800) for communicating information. The methods comprise: storing message sets in Communication Devices (“CDs”) so as to be respectively associated with speaker information; performing operations, by a first CD, to capture an audio message spoken by an individual and to convert the audio message into a message audio file; comparing the message audio file to each reference audio file in the message sets to determine whether one of the reference audio files matches the message audio file by a certain amount; converting the audio message into a text message when a determination is made that a reference audio file does match the message audio file by a certain amount; generating a secure text message by appending the speaker information that is associated with the matching reference audio file to the text message, or by appending other information to the text message; transmitting the secure text message.

Abstract: A method may include obtaining first audio data of a communication session between a first device and a second device and obtaining, during the communication session, a first text string that is a transcription of the first audio data. The method may further include directing the first text string to the first device for presentation of the first text string during the communication session and obtaining, during the communication session, a second text string that is a transcription of the first audio data. The method may further include comparing a first accuracy score of the first word to a second accuracy score of the second word and in response to a difference between the first accuracy score and the second accuracy score satisfying a threshold, directing the second word to the first device to replace the first word in the first location as displayed by the first device.

Abstract: There is provided a computer implemented method of aligning an automatically generated transcription of an audio recording to a manually generated transcription of the audio recording comprising: identifying non-aligned text fragments, each located between respective two non-continuous aligned text-fragments of the automatically generated transcription, each aligned text-fragment matching words of the manually generated transcription, for each respective non-aligned text fragment: mapping a target keyword of the manually generated transcription to phonemes, mapping the respective non-aligned text fragment to a corresponding audio-fragment of the audio recording, mapping the audio-fragment to phonemes, identifying at least some of the phonemes of the audio-fragment that correspond to the phonemes of the target keyword, and mapping the identified at least some of the phonemes of the audio-fragment to a corresponding word of the automatically generated transcript, wherein the corresponding word is an incorrect a

Abstract: Disclosed herein are systems and methods for receiving a voice command and determining an appropriate action for the media playback system to execute based on user identification. The systems and methods receive a voice command for a media playback system, and determines whether the voice command was received from a registered user of the media playback system. In response to determining that the voice command was received from a registered user, the systems and methods configure an instruction for the media playback system based on content from the voice command and information in a user profile for the registered user.

Abstract: Information is read, which relates to an array of objects for input that have been displayed on a display unit upon input of input information. Whether an input object of the input information that is displayed on the display unit has been touched is determined. When the input object is determined as having been touched, the touched input object is recognized as an object to be corrected. A correction candidate object based on the array of the objects for input is displayed in the vicinity of the object to be corrected. Whether the correction candidate object has been touched is determined. When the correction candidate object is determined as having been touched, the object to be corrected is replaced with the touched correction candidate object.

Abstract: A call challenger can receive a user input from a called party identity to opt-in to a call challenge service, and a second user input of a keyword. When the call challenger receives a call directed to a user equipment of the called party identity, the call challenger can prompt the calling party to provide an audible response. In response to a receipt of the audible response, the call challenger can convert the audible response to a text. The call challenger can compare the text with the keyword to determine if there is a sufficient match. In response to the determining the output of the comparing does not satisfy a threshold match score, the call challenger can prevent the call from connecting with the user equipment.