Abstract: Techniques for real-time accent conversion are described herein. An example computing device receives an indication of a first accent and a second accent. The computing device further receives, via at least one microphone, speech content having the first accent. The computing device is configured to derive, using a first machine-learning algorithm trained with audio data including the first accent, a linguistic representation of the received speech content having the first accent. The computing device is configured to, based on the derived linguistic representation of the received speech content having the first accent, synthesize, using a second machine learning-algorithm trained with (i) audio data comprising the first accent and (ii) audio data including the second accent, audio data representative of the received speech content having the second accent.

Abstract: A facility for conveying first side of a voice call from a first participant to a second participant is described. Over the duration of the voice call, the facility receives the first side of the call. The facility seeks to forward the received first side of the voice call to a downstream node on a path to the second participant. The facility records the received first side of the call for at least part of the call. The facility identifies a just-ended portion of the voice call for which forwarding of the received first side of the voice call was unsuccessful. In response, the facility transmits to the downstream node the recorded first side of the voice call that coincides with the identified portion of the voice call.

Abstract: Embodiments described herein relate to an augmented expression system to generate and cause display of a specially configured interface to present an augmented reality perspective. The augmented expression system receives image and video data of a user and tracks facial landmarks of the user based on the image and video data, in real-time to generate and present a 3-dimensional (3D) bitmoji of the user.

Abstract: It is intended to accurately convert a speech rhythm. A model storage unit (10) stores a speech rhythm conversion model which is a neural network that receives, as an input thereto, a first feature value vector including information related to a speech rhythm of at least a phoneme extracted from a first speech signal resulting from a speech uttered by a speaker in a first group, converts the speech rhythm of the first speech signal to a speech rhythm of a speaker in a second group, and outputs the speech rhythm of the speaker in the second group. A feature value extraction unit (11) extracts, from the input speech signal resulting from the speech uttered by the speaker in the first group, information related to a vocal tract spectrum and information related to the speech rhythm.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.

Abstract: A method, a computer program product, and a computer system generate an accurate mental model of an automated agent. The method includes receiving an input from a user device associated with a user during a communication session between the user and the automated agent. The method includes determining a response to the input. The method includes determining a confidence score of the response relative to a confidence threshold. The method includes determining an assertiveness feature associated with the response, the assertiveness feature comprising an expression of the automated agent based on the confidence score. The method includes transmitting the response and the assertiveness feature to the user device, the expression configured to update anthropomorphic characteristics of a graphical representation of the automated agent shown on a graphical user interface of the communication session displayed on a display device of the user device.

Abstract: The present disclosure provides a GAN-based speech synthesis model, a training method, and a speech synthesis method. According to the speech synthesis method, to-be-converted text is obtained and is converted into a text phoneme, the text phoneme is further digitized to obtain text data, and the text data is converted into a text vector to be input into a speech synthesis model. In this way, target audio corresponding to the to-be-converted text is obtained. When a target Mel-frequency spectrum is generated by using a trained generator, accuracy of the generated target Mel-frequency spectrum can reach that of a standard Mel-frequency spectrum. Through constant adversary between the generator and a discriminator and the trainings thereof, acoustic losses of the target Mel-frequency spectrum are reduced, and acoustic losses of the target audio generated based on the target Mel-frequency spectrum are also reduced, thereby improving accuracy of audio synthesized from speech.

Abstract: Aspects of the disclosure relate to using machine learning to simulate an interactive voice response system. A computing platform may receive user interaction information corresponding to interactions between a user and enterprise computing devices. Based on the user interaction information, the computing platform may identify predicted intents for the user, and may generate hotkey information based on the predicted intents. The computing platform may send the hotkey information and commands directing the mobile device to output the hotkey information. The computing platform may receive hotkey input information from the mobile device. Based on the hotkey input information, the computing platform may generate a hotkey response message. The computing platform may send, to the mobile device, the hotkey response message and commands directing the mobile device to convert the hotkey response message to an audio output and to output the audio output.

Abstract: A device may identify a plurality of sources for outputs that the device is configured to provide. The plurality of sources may include at least one of a particular application in the device, an operating system of the device, a particular area within a display of the device, or a particular graphical user interface object. The device may also assign a set of distinct voices to respective sources of the plurality of sources. The device may also receive a request for speech output. The device may also select a particular source that is associated with the requested speech output. The device may also generate speech having particular voice characteristics of a particular voice assigned to the particular source.

Abstract: A hearing aid system presents a hearing impaired user with customized enhanced intelligibility speech sound in a preferred language while maintaining the voice identity of speaker. The system includes a neural network model trained with a set of source speech data representing sampling from a speech population relevant to the user. The model is also custom trained with a set of parallel or non-parallel alternative articulations, collected during an interactive session with user or algorithmically generated based on the hearing profile of the user or category of users with common linguistic and hearing profiles.

Abstract: A hardware decompression acceleration engine including: an input buffer for receiving to-be-decompressed data from a software layer of a host computer; a decompression processing unit coupled to the input buffer for decompressing the to-be-decompressed data, the decompression processing unit further receiving first and second flags from the software layer of the host computer, wherein the first flag is indicative of a location of the to-be-decompressed data in a to-be-decompressed data block and the second flag is indicative of a presence of an intermediate state; and an output buffer for storing decompressed data from the decompression processing unit.

Abstract: An audio signal processing system and method is executed by an audio signal processing device to decode an audio packet to obtain decoded audio and determine an occurrence of a discontinuity occurring with a sudden increase of an amplitude of the decoded audio obtained by decoding the audio packet. The audio packet may be received correctly after an occurrence of a packet loss, and corrected to improve subjective quality of the decoded audio, wherein correcting the discontinuity of the decoded audio comprises causing distances between ISF/LSF parameters corresponding to a frame in which a packet loss has occurred to be equal.

Abstract: Embodiments of a production-quality text-to-speech (TTS) system constructed from deep neural networks are described. System embodiments comprise five major building blocks: a segmentation model for locating phoneme boundaries, a grapheme-to-phoneme conversion model, a phoneme duration prediction model, a fundamental frequency prediction model, and an audio synthesis model. For embodiments of the segmentation model, phoneme boundary detection was performed with deep neural networks using Connectionist Temporal Classification (CTC) loss. For embodiments of the audio synthesis model, a variant of WaveNet was created that requires fewer parameters and trains faster than the original. By using a neural network for each component, system embodiments are simpler and more flexible than traditional TTS systems, where each component requires laborious feature engineering and extensive domain expertise. Inference with system embodiments may be performed faster than real time.

Abstract: Systems, devices, media, and methods are presented for playing audio sounds, such as music, on a portable electronic device using a digital color image of a note matrix on a map. A computer vision engine, in an example implementation, includes a mapping module, a color detection module, and a music playback module. The camera captures a color image of the map, including a marker and a note matrix. Based on the color image, the computer vision engine detects a token color value associated with each field. Each token color value is associated with a sound sample from a specific musical instrument. A global state map is stored in memory, including the token color value and location of each field in the note matrix. The music playback module, for each column, in order, plays the notes associated with one or more the rows, using the corresponding sound sample, according to the global state map.

Abstract: A recording device records a video and an imaging time, and a voice. Based on the voice, a sound parameter calculator calculates a sound parameter for specifying magnitude of the voice in a monitoring area at the imaging time for each of pixels and for each of certain times. A sound parameter storage unit stores the sound parameter. A sound parameter display controller superimposes a voice heat map on a captured image of the monitoring area and displays the superimposed image on a monitor. At this time, the sound parameter display controller displays the voice heat map based on a cumulative time value of magnitude of the voice, according to designation of a time range.

Abstract: An information processing apparatus includes an acquisition unit that acquires voice data and image data, respectively, a display control unit that performs control to display the image data acquired by the acquisition unit in synchronization with the voice data, a reception unit that receives a display element to be added for display to a specific character in the image data displayed by the display control unit, and a setting unit that sets a playback period in which the specific character in the voice data is played back, as a display period of the display element received by the reception unit in the image data.

Abstract: The present disclosure provides method and apparatus for providing personalized songs in automated chatting. A message may be received in a chat flow. Personalized lyrics of a user may be generated based at least on a personal language model of the user in response to the message. A personalized song may be generated based on the personalized lyrics. The personalized song may be provided in the chat flow.

Abstract: Embodiments of systems and methods for providing search term suggestions in a search system are disclosed. Embodiments as disclosed may utilize the sound of an original search term to locate candidate terms based on the sound of the candidate terms and the frequency of appearance of the candidate terms in the corpus of documents being searched. A set of search term suggestions can then be determined from the candidate terms and returned to the user as search term suggestions for the original search term.

Abstract: A method for removing private data from an acoustic model includes capturing speech from a large population of users, creating a text-to-speech voice from at least a portion of the large population of users, discarding speech data from a database of speech, creating text-to-speech waveforms from the text-to-speech voice and the new database of speech with the discarded speech data and generating an automatic speech recognition model using the text-to-speech waveforms.

Abstract: Various embodiments generally relate to systems and methods for creation of voice memos while an electronic device is in a driving mode. In some embodiments, a triggering event can be used to indicate that the electronic device is within a car or about to be within a car and that text communications should be translated (e.g., via an application or a conversion platform) into a voice memo that can be played via a speaker. These triggering events can include a manual selection or an automatic selection based on a set of transition criteria (e.g., electronic device moving above a certain speed, following a roadway, approaching a location in a map of a marked car, etc.).

Abstract: In some embodiments, methods and systems are provided for processing information requests of workers at a retail facility and retrieving information associated with the retail facility based on the information requests. An electronic device permits a worker at the retail facility to input an information request in association with at least one worker at the retail facility or at least one product at the retail facility. A computing device receives, from the electronic device, electronic data representative of a scope of the information request, analyzes this electronic data to determine the scope of the information request, obtain relevant information from one or more databases, and transmits the obtained information to the electronic device, which in turn outputs the information to the worker.

Abstract: A computer functions as: an individual performance data receiver that receives a plurality of pieces of individual performance data from two or more performer user terminals connected via a network, each of the pieces of individual performance data being generated in accordance with a performance operation by a user on the corresponding performer user terminal and transmitted during a performance; a synthetic performance data generator that generates synthetic performance data by synthesizing pieces of individual performance data in an identical time slot, of the plurality of pieces of individual performance data received from the performer user terminals, during the performance, the synthetic performance data being used to reproduce sound in which individual performance contents on the two or more performer user terminals are mixed; and a synthetic performance data transmitter that transmits the synthetic performance data to at least one appreciator user terminal connected via the network during the performa

Abstract: Described herein are embodiments of an end-to-end text-to-speech (TTS) system with parallel wave generation. In one or more embodiments, a Gaussian inverse autoregressive flow is distilled from an autoregressive WaveNet by minimizing a novel regularized Kullback-Leibler (KL) divergence between their highly-peaked output distributions. Embodiments of the methodology computes the KL divergence in a closed-form, which simplifies the training process and provides very efficient distillation. Embodiments of a novel text-to-wave neural architecture for speech synthesis are also described, which are fully convolutional and enable fast end-to-end training from scratch. These embodiments significantly outperform the previous pipeline that connects a text-to-spectrogram model to a separately trained WaveNet. Also, a parallel waveform synthesizer embodiment conditioned on the hidden representation in an embodiment of this end-to-end model were successfully distilled.

Abstract: According to an embodiment, an electronic device includes a user interface, a memory, and a processor. The memory is configured to store a main database including at least one input data or an auxiliary database including at least one category including pieces of response data. The processor is configured to receive a user input, using the user interface, and extract first information from the user input. The processor is also configured to identify whether a portion of the input data of the main database matches the first information. The processor is further configured to identify a category of the user input in response to identifying that the input data of the main database does not match the first information. Additionally, the processor is configured to identify the auxiliary database corresponding to the category, and provide first response data based on an event that the auxiliary database is identified.

Abstract: A speech synthesizer includes a memory configured to store a plurality of sentences and prior information of a word classified into a minor class among a plurality of classes with respect to each sentence, and a processor configured to determine an oversampling rate of the word based on the prior information, determine the number of times of oversampling of the word using the determined oversampling rate and generate sentences including the word by the determined number of times of oversampling. The plurality of classes includes a first class corresponding to first reading break, a second class corresponding to second reading break greater than the first break and a third class corresponding to third reading break greater than the second break, and the minor class has a smallest count among the first to third classes in one sentence.

Abstract: Aspects of the disclosure relate to using machine learning to simulate an interactive voice response system. A computing platform may receive user interaction information corresponding to interactions between a user and enterprise computing devices. Based on the user interaction information, the computing platform may identify predicted intents for the user, and may generate hotkey information based on the predicted intents. The computing platform may send the hotkey information and commands directing the mobile device to output the hotkey information. The computing platform may receive hotkey input information from the mobile device. Based on the hotkey input information, the computing platform may generate a hotkey response message. The computing platform may send, to the mobile device, the hotkey response message and commands directing the mobile device to convert the hotkey response message to an audio output and to output the audio output.

Abstract: This application can provide a method and electronic device for separating mixed sound signal. The method includes: obtaining a first hidden variable representing a human voice feature and a second hidden variable representing an accompaniment sound feature by inputting feature data of a mixed sound extracted from a mixed sound signal into a coding model for the mixed sound; obtaining first feature data of a human voice and second feature data of an accompaniment sound by inputting the first hidden variable and the second hidden variable into a first decoding model for the human voice and a second decoding model for the accompaniment sound respectively; and obtaining, based on the first feature data and the second feature data, the human voice and the accompaniment sound.

Abstract: A method for automatically translating raw data into real human voiced audio content is provided according to an embodiment of the present disclosure. The method may comprise ingesting data, separating the data into or associating the data with a data type, and creating a list of descriptive data associated with the data type. In some embodiments, the method further comprises compiling audio phrases types associated with the descriptive data, associating a pre-recorded audio file with each audio phrase, and merging a plurality of pre-recorded audio files to create a final audio file.

Abstract: An encoding apparatus performing encoding by an encoding process in which bits are preferentially assigned to a low side to obtain a spectrum code, the encoding apparatus judging whether a sound signal is a hissing sound or not, obtaining and encoding, if the encoding apparatus judges that the sound signal is a hissing sound, what is obtained by exchanging all or a part of a spectrum existing on a lower side than a predetermined frequency in a frequency spectrum sequence of the sound signal for all or a part of a spectrum existing on a higher side of the predetermined frequency in the frequency spectrum sequence, the number of all or the part of the high-side frequency spectrum sequence being the same as the number of all or the part of the low-side frequency spectrum sequence.

Abstract: A hand washing supporting device according to embodiments is a hand washing supporting device including a processor, in which the processor is configured to perform a detection process that detects, upon detecting the motion of the hand by the user for a predetermined period of time by the detection process, a motion of a hand by a user, a determination process that determines a start of hand washing by the user, and a notification process that notifies, in accordance with a determination of the start of the hand washing by the determination process, the user of a difference between time required from the start to an end of the hand washing by the user and the predetermined period of time.

Abstract: Methods, systems, computer-readable media, and apparatuses for audio signal processing are presented. Some configurations include determining that first audio activity in at least one microphone signal is voice activity; determining whether the voice activity is voice activity of a participant in an application session active on a device; based at least on a result of the determining whether the voice activity is voice activity of a participant in the application session, generating an antinoise signal to cancel the first audio activity; and by a loudspeaker, producing an acoustic signal that is based on the antinoise signal. Applications relating to shared virtual spaces are described.

Abstract: Methods and systems for customizing a hearing device. The disclosed methods involve receiving an audio sample associated with a target entity, calculating at least one acoustic parameter from the audio sample, generating an audio stimulus using the at least one calculated acoustic parameter, presenting the audio stimulus to a user, receiving a response to the audio stimulus, and adjusting the hearing device based on an optimal parameter.

Abstract: An electronic device and a controlling method of the electronic device are provided. The electronic device acquires text to respond on a received user's speech, acquires a plurality of pieces of parameter information for determining a style of an output speech corresponding to the text based on information on a type of a plurality of text-to-speech (TTS) databases and the received user's speech, identifies a TTS database corresponding to the plurality of pieces of parameter information among the plurality of TTS databases, identifies a weight set corresponding to the plurality of pieces of parameter information among a plurality of weight sets acquired through a trained artificial intelligence model, adjusts information on the output speech stored in the TTS database based on the weight set, synthesizes the output speech based on the adjusted information on the output speech, and outputs the output speech corresponding to the text.

Abstract: A method is performed at a server system of a media-providing service. The server system has one or more processors and memory storing instructions for execution by the one or more processors. The method includes receiving a text sentence including a plurality of words from a device of a first user and extracting a plurality of audio snippets from one or more audio tracks. A respective audio snippet in the plurality of audio snippets corresponds to one or more words in the plurality of words of the text sentence. The method also includes assembling the plurality of audio snippets in a first order to produce an audible version of the text sentence. The method further includes providing, for playback at the device of the first user, the audible version of the text sentence including the plurality of audio snippets in the first order.

Abstract: Provided are a display device and a screen display method for of the display device. In detail, disclosed are a display device capable of controlling a screen thereof through voice recognition, and a screen display method of the display device. Some of the disclosed embodiments provide a display device for displaying, on the screen, a recommendation guide corresponding to the voice recognition result, and a screen display method of the display device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for analyzing ultrasonic signals to recognize mouthed articulations. One of the methods includes generating an ultrasonic carrier signal and coupling the ultrasonic carrier signal to a person's vocal tract. The method includes detecting a modulated ultrasonic signal, the modulated ultrasonic signal corresponding to the ultrasonic carrier signal modulated by the person's vocal tract to include information about articulations mouthed by the person; analyzing, using a data processing apparatus, the modulated ultrasonic signal to recognize the articulations mouthed by the person from the information in the modulated ultrasonic signal; and generating, using the data processing apparatus, an output in response to the recognized articulations.

Abstract: An apparatus for video searching, includes a memory storing instructions, and a processor configured to execute the instructions to split a video into scenes, obtain, from the scenes into which the video is split, one or more textual descriptors describing each of the scenes, encode the obtained one or more textual descriptors describing each of the scenes into a video scene vector of each of the scenes, encode a user query into a query vector having a same semantic representation as that of the video scene vector of each of the scenes into which the one or more textual descriptors describing each of the scenes are encoded, and identify whether the video scene vector of at least one among the scenes corresponds to the query vector into which the user query is encoded.

Abstract: A non-transitory computer-readable recording medium records an output control program for causing a computer to execute processing of: in a case where input of a question is accepted, extracting an accuracy of each of one or a plurality of answers to the question, the accuracy being stored in a storage unit; and selecting an answer to be output from the one or plurality of answers so that a total value of the accuracy of the one or plurality of answers to the question is equal to or larger than a first threshold.

Abstract: A language translation assembly includes a housing that is wearable on a user's ear. A control circuit is positioned within the housing and the control circuit stores a language translation program. A retainer is coupled to the housing and the retainer is positionable around the user's ear for retaining the housing on the user's ear. A microphone is coupled to the housing to sense audile sounds. A speaker is coupled to the housing to emit words translated into the native language of the user when the microphone senses spoken words in a non-native language with respect to the user. The operational software selects an appropriate response in the user's native language from the language database. Additionally, the speaker emits the appropriate response to instruct the user to speak in the non-native language.

Abstract: Embodiments are disclosed for a method for dynamic text reading. The method includes performing pre-processing for a text document. Pre-processing includes determining the text document comprises an emotional statement based on an indicator of an emotion associated with the emotional statement. Pre-processing also includes identifying a speaker of the emotional statement. Further, pre-processing includes generating a role-to-voice map that associates the speaker with a digital representation of a voice for the speaker. The method additionally includes generating, based on the pre-processing, the voice for the speaker reading aloud a text of the text document using the digital representation of the voice with a tonal modulation that conveys the emotion.

Abstract: Methods and systems for generating stateful attacks for simulating and testing security infrastructure readiness. Attack templates descriptive of a plurality of attacks to be executed against one or more targets are defined. The attack templates are processed to compile a decision tree by traversing through a list of attack templates to create a logical tree with tree branches representing different execution paths through which attacks may be executed against the targets. During attack simulations and/or testing, single and/or multi-stage attacks are executed against targets, wherein attack sequences are dynamically determined using the execution paths in the decision tree in view of real-time results. The attacks may be executed against various types of targets, including target in existing security infrastructures and simulated targets. Moreover, the attacks may originate from computer systems within security infrastructures or remotely using computer systems external to the security infrastructures.

Abstract: A method, a computer readable medium, and a computer system are provided for singing voice conversion. Data corresponding to a singing voice is received. One or more features and pitch data are extracted from the received data using one or more adversarial neural networks. One or more audio samples are generated based on the extracted pitch data and the one or more features.

Abstract: A multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N. The multi-channel decorrelator is configured to provide a first set of K? decorrelator output signals on the basis of the second set of K decorrelator input signals. The multi-channel decorrelator is further configured to upmix the first set of K? decorrelator output signals into a second set of N? decorrelator output signals, wherein N?>K?. The multi-channel decorrelator can be used in a multi-channel audio decoder. A multi-channel audio encoder provides complexity control information for the multi-channel decorrelator.

Abstract: Voice cloning is a highly desired capability for personalized speech interfaces. Neural network-based speech synthesis has been shown to generate high quality speech for a large number of speakers. Neural voice cloning systems that take a few audio samples as input are presented herein. Two approaches, speaker adaptation and speaker encoding, are disclosed. Speaker adaptation embodiments are based on fine-tuning a multi-speaker generative model with a few cloning samples. Speaker encoding embodiments are based on training a separate model to directly infer a new speaker embedding from cloning audios, which is used in or with a multi-speaker generative model. Both approaches achieve good performance in terms of naturalness of the speech and its similarity to original speaker—even with very few cloning audios.

Abstract: A speech synthesizer using artificial intelligence includes a memory configured to store a first ratio of a word classified into a minor class among a plurality of classes and a synthesized speech model, and a processor configured to determine a class classification probability set of the word using the word, the first ratio and the synthesized speech model. The first ratio indicates a ratio in which the word is classified into the minor class within a plurality of characters, the plurality of classes includes a first class corresponding to first reading break, a second class corresponding to second reading break greater than the first break and a third class corresponding to third reading break greater than the second break, and the minor class has a smallest count among the first to third classes.

Abstract: Methods and systems are provided for identifying subparts of a text. A neural network system can receive a set of sentences that includes context sentences and target sentences that indicate a decision point in a text. The neural network system can generate context vector sentences and target sentence vectors by encoding context from the set of sentences. These context sentence vectors can be weighted to focus on relevant information. The weighted context sentence vectors and the target sentence vectors can then be used to output a label for the decision point in the text.

Abstract: A method includes obtaining first audio data corresponding to speech occurring within a communication area. The first audio data is obtained from one or more interior locations inside the communication area. The method includes obtaining second audio data corresponding to the speech. The second audio data is obtained from one or more exterior locations outside of the communication area. The method includes calculating a first intelligibility based on the first audio data and calculating a second intelligibility based on the second audio data. The method includes comparing the first intelligibility to the second intelligibility, and determining, based on the comparing, that the second intelligibility exceeds a threshold. The method includes generating a set of countermeasures in response to the determining. The set of countermeasures includes at least one modification to a parameter of the speech. The method includes providing at least one countermeasure of the set of countermeasures.

Abstract: An information processing device according to embodiments includes a communication unit configured to receive audio data of content and text data corresponding to the audio data, an audio data reproduction unit configured to perform reproduction of the audio data, a text data reproduction unit configured to perform the reproduction by audio synthesis of the text data, and a controller that controls the reproduction of the audio data or the text data. The controller causes the text data reproduction unit to perform the reproduction of the text data when the audio data reproduction unit is unable to perform the reproduction of the audio data.

Abstract: There is provided a database management system (DBMS) in order to make anonymization processing of the database efficient. When receiving a query including a conversion rule, the database management system is configured to process a relationship table in the database based on the conversion rule. At that time, the DBMS is configured to acquire data from a processing result table (result of processing the relationship table) stored in the past for tuples the number of which for each value appearing in a predetermined attribute satisfies a condition required for the anonymization processing. On the other hand, for tuples the number of which for each value appearing in a predetermined attribute does not satisfy the condition required for the anonymization processing, the DBMS is configured to acquire data from the database or from a result of processing the relationship table, the result being stored in rather than the processing result table.

Abstract: [Problem] To allow a user to grasp clearly a source of information with sound. [Solution] There is provided an information processor that includes an output control unit that controls output of an information notification using sound, the output control unit causing, on the basis of a recognized external sound source, the information notification to be output in an output mode that is not similar to an external sound that can be emitted by the external sound source. There is also provided an information processing method that includes controlling, by a processor, output of an information notification using sound, the controlling further including causing, on the basis of a recognized external sound source, the information notification to be output in an output mode that is not similar to an external sound that can be emitted by the external sound source.