Abstract: Methods, systems, and apparatus, for generated labeled training examples for machine learning. In one aspect, a method includes receiving sets of audio recordings by a user device. For each set of audio recordings, each audio recording in the set is recorded over a respective separate microphone in the user device during a particular time interval, and each particular time interval is different for each set of audio recordings. For each set of audio recordings, a detector determines whether an audio recording in the set of audio recordings includes a particular audio feature, and whether another one of the audio recordings does not include the particular audio feature. For each set of audio recordings determined to include an audio recording that includes the particular audio feature and to include another audio recording that does not include the particular audio feature, a labeled training example is generated.

Abstract: Techniques for user authentication via in-ear acoustic measurements are disclosed. An in-ear device emits an acoustic signal and detects an otic response to the acoustic signal. A user signature is generated based at least on the otic response to the acoustic signal. The user signature is compared with a reference signature, to determine whether the in-ear device has changed users.

Abstract: A method and apparatus for training a speech recognition model, an electronic device and a storage medium are provided.

Abstract: Methods, systems, and computer-readable media for event extraction from documents with co-reference are disclosed. An event extraction service identifies one or more trigger groups in a document comprising text. An individual one of the trigger groups comprises one or more textual references to an occurrence of an event. The one or more trigger groups are associated with one or more semantic roles for entities. The event extraction service identifies one or more entity groups in the document. An individual one of the entity groups comprises one or more textual references to a real-world object. The event extraction service assigns one or more of the entity groups to one or more of the semantic roles. The event extraction service generates an output indicating the one or more trigger groups and one or more entity groups assigned to the semantic roles.

Abstract: A computer-implemented system and method relate to natural language processing. A candidate is selected based on a query. The candidate includes a question and an answer to that question. The candidate is classified as belonging to a class. The class indicates that the candidate is relevant to the query. The class is selected from among a group of classes, which includes at least that class and another class. The another class indicates that the candidate has the answer to the query. Upon classifying the candidate as belonging to the class, a machine learning system is configured to generate a relevant response for the query upon receiving the query and the question as input data. The relevant response provides information associated with a keyword of the question that is not contained in the query.

Abstract: Described herein are techniques, devices, and systems for training a machine learning model(s) and/or artificial intelligence algorithm(s) to determine where a mobile device (and, hence, a user of the mobile device) is located based on audio data associated with the mobile device and/or contextual data associated with the mobile device. The machine learning techniques may be used to determine contextual information about users, such as determining that a particular location is likely to be a user's home, office, or the like, based on movement patterns exhibited in the data associated with a user's mobile device. Once trained, the machine learning model(s) is usable to classify a mobile device as having been located at one of multiple candidate locations, such as indoors or outdoors, at a particular time. The described techniques can improve the accuracy of determining a mobile device's location, among other technical benefits.

Abstract: A hearing instrument includes: a first portion shaped and sized for placement at a pinna of a user's ear; and a second portion having an earpiece for placement in the user's ear canal; wherein the second portion also comprises a connector assembly configured for electrically coupling to the first portion, the connector assembly having a plurality of connector wires, the plurality of connector wires comprising a first connector wire; wherein the second portion also comprises a receiver or miniature loudspeaker for receipt of an audio drive signal through at least the first connector wire; and wherein the second portion also comprises a non-volatile memory circuit having a data interface configured for receipt and transmittal of module data, the non-volatile memory circuit configured to store the module data, wherein the stored module data at least comprises electroacoustic calibration parameter(s) of the receiver or the miniature loudspeaker.

Abstract: Methods and systems are provided for automatically, via an artificial-intelligence bot, receiving a query made by a participant in a conference meeting, determine one or more subject matter experts to contact outside of the conference meeting, receive a response to the query from at least one of the subject matter experts, and present the response to the query to the participants of the conference meeting. The artificial-intelligence bot presents the response to the query while the conference meeting is in progress without any participant of the conference meeting communicating with the subject matter expert, without ever connecting a client device of the subject matter expert to the conference meeting, and without ever including the subject matter expert in the conference meeting.

Abstract: Various examples are directed to systems and methods for detecting potentially fraudulent voice calls to a financial services institution. A computing system may receive an indication of a voice call placed by a voice caller to an operator. The computing system may generate a network address indicator describing a network location. The network address indicator may be provided to the voice caller. The computing system may receive an indication of a financial services account indicated by the voice caller. The computing system may also receive an indication of an access to the network location by a remote device. The computing system may determine, using the indication of the access to the network location, a first location associated with the remote device and determine that the first location does not match a second location associated with the financial services account. The computing system may generate an alert indicating that the voice call is potentially fraudulent.

Abstract: Systems and methods are presented herein for generating a new language understanding model, based on a user request. A user may input a root language and a locale into an application for generating a student language model. The application may generate the student language model and may identify a teacher language model related to the student language model. The application may compare data from the identified teacher language model to the student language model. The application may determine a subset of data from the teacher language model is not contained in the student language model. If the application determines at least a subset of data from the teacher language model is not in the student language model, the application may add at least the subset of data from the teacher language model to the student language model.

Abstract: A method, computer system, and a computer program product for chatbot generating is provided. The present invention may include determining one or more entities based on at least one column header of a dataset. The present invention may include determining one or more actions based on an associated row, the associated row corresponding to the at least one column header. The present invention may include generating a conversation environment, wherein the conversation environment comprises pairing the one or more entities with the one or more supplied intents of a chatbot workspace and pairing the one or more actions with one or more supplied utterances of the chatbot workspace.

Abstract: The present disclosure provides methods and systems that may be used for providing quality control for audio samples. The audio samples may be speech samples of a user. The user may be participating in an audio interview.

Abstract: A feedback noise reduction method, a feedback noise reduction system, and an earphone are provided. In the method, a channel morphological parameter of an acoustic channel between a microphone and a speaker in a feedback noise reduction system is detected; the feedback noise reduction system is switched from using a first noise reduction filter to using a second noise reduction filter in a case that it is determined that the acoustic channel is in an interfered state based on the channel morphological parameter; and a noise reduction signal is generated by using the second noise reduction filter to cancel a noise signal received by the feedback noise reduction system. A frequency response of the second noise reduction filter in a predetermined frequency band is less than a frequency response of the first noise reduction filter in the predetermined frequency band.

Abstract: A system and method for dynamically providing safe call back numbers to use to respond to an inbound communication, the method comprising parsing message records from a message server, analyzing the message records for untrustworthy phone numbers by comparing content of the message records to a reference data set that is retrieved from a database, the reference data set including genuine and fraud data wherein the genuine and fraud data includes entities and contact information corresponding to the entities, determining untrustworthy phone numbers in the message records from the analysis, and generating remedy actions based on the determination of the untrustworthy phone numbers.

Abstract: An apparatus comprising means for: receiving values for sub-bands of a frame of an audio signal, the values comprising at least one azimuth value, at least one elevation value at least one energy ratio value and at least one spread and/or surround coherence value for each sub-band; determining a codebook for encoding at least one spread and/or surround coherence value for each sub-band based on the at least one energy ratio value and at least one azimuth value for each sub-band for a frame; discrete cosine transforming at least one vector, the at least one vector comprising the at least one spread and/or surround coherence value for a sub-band for the frame; and encoding a first number of components of the discrete cosine transformed vector based on the determined codebook.

Abstract: A virtual assistant system for communicating with customers uses human intelligence to correct any errors in the system AI, while collecting data for machine learning and future improvements for more automation. The system may use a modular design, with separate components for carrying out different system functions and sub-functions, and with frameworks for selecting the component best able to respond to a given customer conversation.

Abstract: The present disclosure provides a multi-lingual model training method, apparatus, electronic device and readable storage medium and relates to the technical field of deep learning and natural language processing. A technical solution of the present disclosure when training the multi-lingual model is: obtaining training corpuses comprising a plurality of bilingual corpuses and a plurality of monolingual corpuses; training a multi-lingual model with a first training task by using the plurality of bilingual corpuses; training the multi-lingual model with a second training task by using the plurality of monolingual corpuses; and completing the training of the multi-lingual model in a case of determining that loss functions of the first training task and second training task converge.

Abstract: A conference participant is alerted as to an event during a conference responsive to a determination that a focus of the conference participant is other than on the conference. During the conference, an event associated with the conference participant is detected based on a real-time transcription of the conference. For example, the event may relate to a topic relevant to the conference participant or a request associated with a name of the conference participant. A determination is made that a focus of the conference participant is other than on the conference based on information associated with a device of the conference participant, such as input received from a camera associated with the device or a setting of an audio output device associated with the device. Based on that determination and the detected event, output is presented to alert the conference participant as to the event.

Abstract: A method of detecting a pattern in common in two text files, each comprising an ordered sequence of words, is disclosed. The method includes generating groups of words having the same syntactic function, comprising at least one word from each text file such that each word in a group is synonymous with another word in the same group, associating each word in a text file belonging to a group of words with a tag representative of the group, generating, for each text file, at least one dense set of words satisfying a condition of internal proximity in the text file, determining at least one pattern in common in the two text files, a pattern in common including one or more sets of words sharing the same tag and comprising at least one word from a dense set of words in each text file.

Abstract: In order to achieve a music providing system capable of controlling the behavioral state of a non-human animal using music, this music providing system for a non-human animal is provided with: a state information acquisition unit for acquiring state information relating to the motion state of an animal of interest; a state estimation processing unit for estimating the current behavioral state of the animal of interest from the state information; a target state storage unit for storing information relating to a target behavioral state for the animal of interest; a sound source storage unit for storing multiple music information pieces; a music information selection unit for detecting the degree of divergence of the current behavioral state from the target behavioral state and selecting one specific music information piece on the basis of the multiple music information pieces stored in the sound source storage unit; and a music information output unit for outputting the specific music information by wireless co