Abstract: A computer-implemented method is provided for generating a language model for an application. The method includes estimating interpolation weights of each of a plurality of language models according to an Expectation Maximization (EM) algorithm based on a first metric. The method further includes classifying the plurality of language models into two or more sets based on characteristics of the two or more sets. The method also includes estimating a hyper interpolation weight for the two or more sets based on a second metric specific to the application. The method additionally includes interpolating the plurality of language models using the interpolation weights and the hyper interpolation weight to generate a final language model.

Abstract: Systems, apparatuses, and methods are described for a privacy blocking device configured to prevent receipt, by a listening device, of video and/or audio data until a trigger occurs. A blocker may be configured to prevent receipt of video and/or audio data by one or more microphones and/or one or more cameras of a listening device. The blocker may use the one or more microphones, the one or more cameras, and/or one or more second microphones and/or one or more second cameras to monitor for a trigger. The blocker may process the data. Upon detecting the trigger, the blocker may transmit data to the listening device. For example, the blocker may transmit all or a part of a spoken phrase to the listening device.

Abstract: Systems, apparatuses, and methods are described for a privacy blocking device configured to prevent receipt, by a listening device, of video and/or audio data until a trigger occurs. A blocker may be configured to prevent receipt of video and/or audio data by one or more microphones and/or one or more cameras of a listening device. The blocker may use the one or more microphones, the one or more cameras, and/or one or more second microphones and/or one or more second cameras to monitor for a trigger. The blocker may process the data. Upon detecting the trigger, the blocker may transmit data to the listening device. For example, the blocker may transmit all or a part of a spoken phrase to the listening device.

Abstract: An aircraft noise monitoring system uses a set of geographically distributed noise sensors to receive data corresponding to events captured by the noise sensors. Each event corresponds to noise that exceeds a threshold level. For each event, the system will receive a classification of the event as an aircraft noise event or a non-aircraft noise event. It will then use the data corresponding to the events and the received classifications to train a convolutional neural network (CNN) in a classification process. After training, when the system receives a new noise event, it will use the CNN to classify the new noise event as an aircraft noise event or a non-aircraft noise event, and it will generate an output indicating whether the new noise event is an aircraft noise event or a non-aircraft noise event.

Abstract: An embodiment includes converting an original audio signal to an original text string, the original audio signal being from a recording of the original text string spoken by a specific person in a source language. The embodiment generates a translated text string by translating the original text string from the source language to a target language, including translation of a word from the source language to a target language. The embodiment assembles a standard phoneme sequence from a set of standard phonemes, where the standard phoneme sequence includes a standard pronunciation of the translated word. The embodiment also associates a custom phoneme with a standard phoneme of the standard phoneme sequence, where the custom phoneme includes the specific person's pronunciation of a sound in the translated word. The embodiment synthesizes the translated text string to a translated audio signal including the translated word pronounced using the custom phoneme.

Abstract: A jitter buffer control for controlling a provision of a decoded audio content on the basis of an input audio content is configured to select a frame-based time scaling or a sample-based time scaling in a signal-adaptive manner. An audio decoder uses such a jitter buffer control.

Abstract: Conversational understanding systems allow users to conversationally interface with a computing device. In examples, a query may be received that includes a request for execution of a task. A data exchange task definition may be accessed. The data exchange task definition assists a conversational understanding system in managing task state tracking for information needed for task execution. Using the data exchange task definition, a per-turn policy for interacting with the user computing device is generated based on the state of a dialogue with a computing device and an evaluation of a process flow chart provided by a task owner resource. The task owner resource may be independent from the conversational understanding system. A response to the query may be generated and output based on the per-turn policy. In examples, the per-turn policy is used to generate one or more responses during a dialogue with a user via a computing device.

Abstract: A system including sensors configured to provide physiological markers of a developer and a controller configured provide information indicative of a user experience to the developer while receive signals from the sensors. The controller is configured to utilize cognitive analysis determine developer emotion responses as the developer receives the user experience. The controller compares a developer emotion classification with a user emotion classification of a user as the user generated the user experience. The system generates a prioritized backlog to identify points where emotion responses between user and developer are in common, or where emotion responses between user and developer differ.

Abstract: Generally, the present disclosure is directed to systems and methods for performing task-oriented response generation that can provide advantages for artificial intelligence systems or other computing systems that include natural language processing for interpreting user input. Example implementations can process natural language descriptions of various services that can be accessed by the system. In response to a natural language input, systems can identify relevant values for executing one of the service(s), based in part on comparing embedded representations of the natural language input and the natural language description using a machine learned model.

Abstract: An electronic apparatus is disclosed. The electronic apparatus includes a display, a storage in which keyword information by product specification is stored, and a processor configured to obtain user feedback on the product by crawling a website, identify positive feedback or negative feedback among the user feedback corresponding to the keyword information by specification by performing natural language processing (NLP) to which at least two different algorithms are applied, and display a result of the identification through the display.

Abstract: Systems, apparatuses, and methods for capturing voice messages are provided. In one embodiment, a method can include receiving, by one or more processors of a mobile user device, a user input indicative of a voice message at a first time. The method can further include identifying contextual data indicative of one or more computing devices within proximity of the mobile user device. The method can include providing a set of data for storage in one or more memory devices of the mobile user device. The set of data can indicate the voice message and the contextual data indicative of the computing devices. The method can further include providing an output indicative of the voice message and the contextual data to one or more secure computing devices at a second time.

Abstract: The subject matter of this specification can be embodied in, among other things, a method that includes receiving an audio signal and initiating speech recognition tasks by a plurality of speech recognition systems (SRS's). Each SRS is configured to generate a recognition result specifying possible speech included in the audio signal and a confidence value indicating a confidence in a correctness of the speech result. The method also includes completing a portion of the speech recognition tasks including generating one or more recognition results and one or more confidence values for the one or more recognition results, determining whether the one or more confidence values meets a confidence threshold, aborting a remaining portion of the speech recognition tasks for SRS's that have not generated a recognition result, and outputting a final recognition result based on at least one of the generated one or more speech results.

Abstract: An example method of automated selection of audio asset synthesizing pipelines includes: receiving an audio stream comprising human speech; determining one or more features of the audio stream; selecting, based on the one or more features of the audio stream, an audio asset synthesizing pipeline; training, using the audio stream, one or more audio asset synthesizing models implementing respective stages of the selected audio asset synthesizing pipeline; and responsive to determining that a quality metric of the audio asset synthesizing pipeline satisfies a predetermined quality condition, synthesizing one or more audio assets by the selected audio asset synthesizing pipeline.

Abstract: Embodiments provide systems and methods for navigating a dialogue flow using a trained intelligence bot. Upon initiation of a chat session between a user and a trained intelligence bot, one or more utterances can be received. The utterances can be processed using the trained intelligence bot to resolve an intent from among a plurality of predefined intents, where the intelligence bot is trained to resolve predefined intents based on training data associated with the predefined intents. A predefined dialogue flow associated with the resolved intent can be navigated using the intelligence bot, where the intelligence bot guides the user through the dialogue flow using context variables that are associated with the user or the chat session. The user can be provided enterprise data retrieved by the intelligence bot using a retrieval request generated based on one or more of the navigation of the dialogue flow or the context variables.

Abstract: Media, methods, and systems are provided for audio rerouting to echo cancel audio in web browsers hosting video streams. Spoken audio from a presenter in a video stream may be received via a microphone on a presenter computing device using a first audio connection. Echo cancellation for the presenter may be enabled. Media audio from the presenter may be received originating from a second audio connection. In response to receiving the media audio, a loopback connection for the presenter may be created. In the loopback connection, the presenter may act as both the sender and receiver of the media audio. The loopback connection may have echo cancellation enabled and use the first audio connection. Once the loopback connection is created, the audio may be routed through the loopback connection. The audio may then be played out of an audio output device for the presenter with echo cancellation enabled.

Abstract: Systems, apparatuses, and methods are described for a privacy blocking device configured to prevent receipt, by a listening device, of video and/or audio data until a trigger occurs. A blocker may be configured to prevent receipt of video and/or audio data by one or more microphones and/or one or more cameras of a listening device. The blocker may use the one or more microphones, the one or more cameras, and/or one or more second microphones and/or one or more second cameras to monitor for a trigger. The blocker may process the data. Upon detecting the trigger, the blocker may transmit data to the listening device. For example, the blocker may transmit all or a part of a spoken phrase to the listening device.

Abstract: An audio recognition method, including: acquiring an audio file to be recognized (S100); extracting audio feature information of the audio file to be recognized, the audio feature information including audio fingerprints (S200); searching, in a fingerprint index database, audio attribute information matched with the audio feature information, the fingerprint index database including an audio fingerprint set in which invalid audio fingerprint removal has been performed on audio sample data (S300). As the audio fingerprint set in the fingerprint index database has been subjected to invalid audio fingerprint removal of audio sample data, the storage space of audio fingerprints in the fingerprint index database can be reduced, and the audio recognition efficiency can be improved. Further provided are an audio recognition device and a server.

Abstract: Systems, apparatuses, and methods are described for a privacy blocking device configured to prevent receipt, by a listening device, of video and/or audio data until a trigger occurs. A blocker may be configured to prevent receipt of video and/or audio data by one or more microphones and/or one or more cameras of a listening device. The blocker may use the one or more microphones, the one or more cameras, and/or one or more second microphones and/or one or more second cameras to monitor for a trigger. The blocker may process the data. Upon detecting the trigger, the blocker may transmit data to the listening device. For example, the blocker may transmit all or a part of a spoken phrase to the listening device.

Abstract: An electronic apparatus is provided. The electronic apparatus includes a communicator comprising communication circuitry configured to communicate with a voice recognition server; and a processor configured to control the communicator to establish a session with the voice recognition server, based on a voice input start signal being received from a first external apparatus, to maintain the established session based on the voice input start signal being received from a second external apparatus in a state where the session is established, and to process voice recognition on audio data received from the second external apparatus using the maintained session.

Abstract: A method may include generating word string vectors for word strings in a document, obtaining encrypted word string vectors by encrypting the word string vectors, generating a search vector for a search query, obtaining an encrypted search vector by encrypting the search vector, calculating encrypted distances between the encrypted word string vectors and the encrypted search vector, obtaining a decrypted distance by decrypting an encrypted distance, and using the decrypted distance, determining a semantic match between the search query and the document.