Abstract: Disclosed is a method of editing a speech recognition result, the method being performed by a computing device. The method may include: displaying a word list satisfying a predetermined condition based on text information generated by speech recognition; determining a target word within the word list; and displaying a region corresponding to the target word within the text information, in which the predetermined condition includes at least one of predetermined word information for each user account and predetermined threshold information associated with a frequency of occurrence of a word.

Abstract: Disclosed are a method, a device, and a program for selecting a main speaker among speakers included in a sound source or a conversation record based on the sound source or the conversation record including conversation contents of at least one speaker and generating a summary based on the main speaker. A method of generating a summary for a sound source, the method being performed by at least one computing device, includes: generating a speak score for at least one speaker based on the sound source; determining a main speaker of the sound source based on a speak score for said at least one speaker; and generating a summary for the sound source in consideration of the determined main speaker.

Abstract: Disclosed is a method for identifying a word corresponding to a target word in text information, which is performed by one or more processors of a computing device. The method may include: determining a target word; determining a threshold for an edit distance associated with the target word; determining a word of which the edit distance from the target word among words included in text information is equal to or less than the threshold; and identifying the word corresponding to the target word based on the determined word.

Abstract: Disclosed is a method of correcting text information. The method can be performed by a computing device. The method includes obtaining the text information. The method includes determining problem text within the text information. The method includes generating alternative text to correct the problem text by utilizing expanded text associated with the problem text or non-text type information associated with the problem text. The method includes providing information about the alternative text for correcting the problem text.

Abstract: Disclosed is a pronunciation transcription method performed by a computing device. The method may include: acquiring a partial audio signal of a first sound unit generated by splitting an audio signal; inputting the partial audio signal of the first sound unit into a pronunciation transcription model; and outputting a pronunciation transcription result for the partial audio signal of the first sound unit by using the pronunciation transcription model.

Abstract: Disclosed is a method for determining important parts among a speech-to-text (STT) result and reference data, which is performed by a computing device. The method may include acquiring STT data generated by performing STT with respect to a speech signal; acquiring reference data; determining first important information in one data among the STT data and the reference data; and determining second important information linked with the first important information in other data different from data in which the first important information is determined among the STT data and the reference data.

Abstract: Disclosed is a voice recognition method based on a neural network, performed by one or more processors of a computing device. The voice recognition method includes generating first text data based on a first language based on voice information. The method includes detecting problem text among the generated first text data. The method includes detecting a second language corresponding to the detected problem text. The method includes generating second text data based on the detected second language, in which the second language is different from the first language.

Abstract: Disclosed is a method for detecting a speech segment, which is performed by a computing device. The method may include: detecting a start point of a speech segment in an audio signal; and detecting an end point of the speech segment based on an offset threshold which is dynamically changed, and the dynamically changed offset threshold may be based on a length of the speech segment.

Abstract: Disclosed is a method for determining a content associated with a voice signal, which is performed by a computing device. The method may include converting a voice signal and generating text information. The method may include determining a plurality of target word candidates. The method may include determining a target word among the plurality of target word candidates based on a comparison between the plurality of target word candidates and the generated text information. The method may also include determining a content associated with the target word.

Abstract: Disclosed is a method for detecting a voice from audio data, performed by a computing device according to an exemplary embodiment of the present disclosure. The method includes obtaining audio data; generating image data based on a spectrum of the obtained audio data; analyzing the generated image data by utilizing a pre-trained neural network model; and determining whether an automated response system (ARS) voice is included in the audio data, based on the analysis of the image data.

Abstract: Disclosed is a method for generating data, the method is performed by one or more processors of a computing device. The method may include: segmenting text data generated based on speech information into a token unit; generating a first feature vector based on the text data segmented into the token unit, and generating a first label vector corresponding to the generated first feature vector, and generating a second feature vector and a second label vector by performing mix-up for each of the generated first feature vector and the generated first label vector.

Abstract: Disclosed is a speech recognition method performed by one or more processors of a computing device, the speech recognition method including: performing first speech recognition on voice information to obtain first text information on the voice information; receiving feedback regarding the first text information; and generating final text information for the voice information based on the received feedback, in which the first speech recognition includes real-time speech recognition, and is performed through a neural network model of a first structure.

Abstract: Disclosed is a method for dialogued summarization with word graphs, which is performed by one or more processors of a computing device. The method may include: generating a word graph based on information on a dialogue which is a summary target; extracting at least one keyword based on the generated word graph; generating a plurality of candidate summary sentences based on the generated word graph; and calculating a score associated with at least one keyword for each of the plurality of candidate summary sentences, and selecting at least one of the plurality of candidate summary sentences based on the calculated score.