Aspects relate to apparatuses and methods for selectively inserting text into a video resume. An exemplary apparatus includes a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive a video resume from a user, divide the video resume is into temporal sections, acquire a plurality of textual inputs from a user, wherein the plurality of textual inputs pertains to the same user of received video resume, classify the plurality of textual inputs to corresponding temporal sections of the received video resume and display, as a function of the classification, the received video resume with a corresponding plurality of textual inputs.

A method includes: receiving, by a computing device, a digital voice stream; receiving, by the computing device, converted text that represents the digital voice stream; identifying, by the computing device, an erroneously converted portion of the converted text; selecting, by the computing device, the erroneously converted portion for explainability processing; parsing, by the computing device, the erroneously converted portion into parts based on a predetermined parsing level; collecting, by the computing device, supplementary input data related to the erroneously converted portion; and determining, by the computing device and based on the supplemental input data, a reason why the erroneously converted portion was erroneously converted.

Systems and processes for identifying of a voice input providing one or more user credentials are provided. In one example process, a voice input can be received. A first character, a phrase identifying a second character, and a word can be identified based on the voice input. In response to the identification, the first character, the second character, and the word can be converted to text. The text can be caused to display, with a display, in a sequence corresponding to an order of the first character, the second character, and the word in the voice input.

Implementations are directed to causing a voice bot to utilize a plurality of ML layers in resolving unique personal identifier(s) for a human while the voice bot is engaged in a corresponding conversation with the human. The unique personal identifier(s) can include a unique sequence of alphanumeric characters that is personal to the human. In some implementations, ASR speech hypothes(es) corresponding to spoken utterance(s) that include the unique personal identifier(s) can be processed to generate candidate unique personal identifier(s), given alphanumeric character(s) of the candidate unique personal identifier(s) can be selected, and the voice bot can prompt the human with clarification request(s) to clarify the given alphanumeric character(s) until it is predicted to correspond to the an actual unique personal identifier(s) for the human(s). The unique personal identifier(s) can then be utilized in performance of further action(s) by the voice bot and/or other systems.

A system comprising: an input configured to receive input speech data originating from a user; an output configured to output speech or text information; and a processor configured to: provide first input data to a character sequence determination module to determine a character sequence from the first input data, wherein determining a character sequence comprises: obtaining a first list of one or more candidate character sequences from the first input data; selecting a first candidate character sequence from the first list; generating a first confirm request to confirm the selected first candidate character sequence, wherein the first confirm request is outputted by way of the output; if second input data indicating that the first candidate character sequence is not confirmed is received, selecting a second candidate character sequence and generating a second confirm request to confirm the selected second candidate if the second candidate character sequence is different from the first candidate character sequence, wherein the second confirm request is outputted by way of the output; and if second input data indicating that the first candidate character sequence is confirmed is received, the one or more processors are further configured to: provide third input data to a dialogue module, wherein the dialogue module is configured to: determine, based on the third input data, a dialogue act that specifies speech or text information; and output, by way of the output, the speech or text information specified by the determined dialogue act.

Disclosed are an information providing device and an information providing method, which provide information enabling a conversation with a user by executing an artificial intelligence (AI) algorithm and/or a machine learning algorithm in a 5G environment connected for Internet-of-Things. An information providing method according to one embodiment of the present disclosure includes gathering first situational information from a home monitoring device, gathering, from the first electronic device, second situational information corresponding to the first situational information, gathering, from the home monitoring device, third situational information containing a behavioral change of the user after gathering the first situational information, generating a spoken sentence to provide to the user on the basis of the first situational information to the third situational information, and converting the spoken sentence to spoken utterance information to be output to the user.

Systems and methods for correcting recognition errors in speech recognition systems are disclosed herein. Natural conversational variations are identified to determine whether a query intends to correct a speech recognition error or whether the query is a new command. When the query intends to correct a speech recognition error, the system identifies a location of the error and performs the correction. The corrected query can be presented to the user or be acted upon as a command for the system.

In one embodiment, a system includes an automatic speech recognition (ASR) module, a natural-language understanding (NLU) module, a dialog manager, one or more agents, an arbitrator, a delivery system, one or more processors, and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to receive a user input, process the user input using the ASR module, the NLU module, the dialog manager, one or more of the agents, the arbitrator, and the delivery system, and provide a response to the user input.

Aspects relate to apparatuses and methods for selectively inserting text into a video resume. An exemplary apparatus includes a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive a video resume from a user, divide the video resume is into temporal sections, acquire a plurality of textual inputs from a user, wherein the plurality of textual inputs pertains to the same user of received video resume, classify the plurality of textual inputs to corresponding temporal sections of the received video resume and display, as a function of the classification, the received video resume with a corresponding plurality of textual inputs.

Systems and methods for efficient management of an audio/video conferences is disclosed. The method includes receiving an audio question from a first user of a plurality of users connected to a conference, recording the audio question and preventing an immediate transmission of the audio question to the plurality of users connected to the conference, analyzing the recorded question and a recorded portion of the conference to determine that the question has been answered during the recorded portion of the conference, and in response to the determining that the audio question has previously been answered, transmitting a relevant section of the recorded portion of the conference consisting of an answer to the audio question to the first user.