The application describe a data processing system and associated methods for processing received speech data. The data processing system comprises: a classification unit configured to receive data derived from an audio signal and, based on the received data, to determine a classification state of an acoustic environment; wherein access to a subsequent processing unit is controlled based on the classification state of the acoustic environment. The classification state may be derived based on a pre-trained model, wherein the representation comprises a representation of the direct to reverberant ratio (DRR) of the audio signal.

A method, system, and phonetic search engine are described that enable phonetic searches to have increased relevancy to the searcher. Specifically, phonetic searches on a database containing phonetically-searchable content can have one or more phonetically-confusable terms included therein, thereby creating search results that more faithfully reflect the search terms used during the phonetic search of the database.

A robust digital fingerprint of a file ensures that one able to produce the robust digital fingerprint has possession of the file. A client obtains information that is unpredictable to the client and uses that information to modify the file and generate a robust digital fingerprint from the modified file. A server, with access to the same unpredictable information, verifies the generated robust digital fingerprint. An algorithm for generating the robust digital fingerprint has a property that different representations of the same content will produce matching digital fingerprints.

Methods, apparatus, systems and articles of manufacture are disclosed to identify media that has been pitch shifted, time shifted, and/or resampled. An example apparatus includes: memory; instructions in the apparatus; and processor circuitry to execute the instructions to: transmit a fingerprint of an audio signal and adjusting instructions to a central facility to facilitate a query, the adjusting instructions identifying at least one of a pitch shift, a time shift, or a resample ratio; obtain a response including an identifier for the audio signal and information corresponding to how the audio signal was adjusted; and change the adjusting instructions based on the information.

Implementations set forth herein relate to an automated assistant that allows a user to create, edit, and/or share documents without directly interfacing with a document editing application. The user can provide an input to the automated assistant in order to cause the automated assistant to interface with the document editing application and create a document. In order to identify a particular action to perform with respect to a document, and/or identify a particular subsection within the document to direct the action, the automated assistant can rely on semantic annotations. As a user continues to interact with the automated assistant to edit a document, the semantic annotations can be updated according to how the document is changing and/or how the user refers to the document. This can allow the automated assistant to more readily fulfill document-related requests that may lack express details.

Implementations set forth herein relate to an automated assistant that allows a user to create, edit, and/or share documents without directly interfacing with a document editing application. The user can provide an input to the automated assistant in order to cause the automated assistant to interface with the document editing application and create a document. In order to identify a particular action to perform with respect to a document, and/or identify a particular subsection within the document to direct the action, the automated assistant can rely on semantic annotations. As a user continues to interact with the automated assistant to edit a document, the semantic annotations can be updated according to how the document is changing and/or how the user refers to the document. This can allow the automated assistant to more readily fulfill document-related requests that may lack express details.

A machine accesses audio data that may be included in a media item, and the audio data includes multiple segments. The machine detects a silent segment among non-silent segments of the audio data. The machine generates sub-fingerprints of the non-silent segments by hashing the non-silent segments with a same fingerprinting algorithm, but the machine generates a sub-fingerprint of the silent segment based on a predetermined non-zero value that represents fingerprinted silence. With these sub-fingerprints generated, the machine generates a fingerprint of the audio data, of the media item, or of both, by storing the generated sub-fingerprints mapped to locations of their corresponding segments in the audio data. The machine then indexes the fingerprint by indexing the sub-fingerprints of the non-silent segments, without indexing the sub-fingerprint of the silent segment.

A machine accesses audio data that may be included in a media item, and the audio data includes multiple segments. The machine detects a silent segment among non-silent segments of the audio data. The machine generates sub-fingerprints of the non-silent segments by hashing the non-silent segments with a same fingerprinting algorithm, but the machine generates a sub-fingerprint of the silent segment based on a predetermined non-zero value that represents fingerprinted silence. With these sub-fingerprints generated, the machine generates a fingerprint of the audio data, of the media item, or of both, by storing the generated sub-fingerprints mapped to locations of their corresponding segments in the audio data. The machine then indexes the fingerprint by indexing the sub-fingerprints of the non-silent segments, without indexing the sub-fingerprint of the silent segment.

The present disclosure relates to a method performed by a hazard reporting system for enabling a vehicle occupant to, in an un-distractive and dynamic manner, report a hazard associated with the surroundings of a vehicle. The hazard reporting system receives a verbal hazard report from the vehicle occupant, which verbal hazard report comprises information related to a hazard associated with the surroundings of the vehicle. The hazard reporting system further transforms, with support from a speech recognition service, the verbal hazard report into a resulting machine-readable hazard report. The hazard reporting system further provides a data set comprising one or more hazard categories. Moreover, the hazard reporting system determines, when identifying a hazard category of the data set considered corresponding to the machine-readable hazard report, that the corresponding hazard category represents the hazard reported in the verbal hazard report.

The present disclosure relates to a method performed by a hazard reporting system for enabling a vehicle occupant to, in an un-distractive and dynamic manner, report a hazard associated with the surroundings of a vehicle. The hazard reporting system receives a verbal hazard report from the vehicle occupant, which verbal hazard report comprises information related to a hazard associated with the surroundings of the vehicle. The hazard reporting system further transforms, with support from a speech recognition service, the verbal hazard report into a resulting machine-readable hazard report. The hazard reporting system further provides a data set comprising one or more hazard categories. Moreover, the hazard reporting system determines, when identifying a hazard category of the data set considered corresponding to the machine-readable hazard report, that the corresponding hazard category represents the hazard reported in the verbal hazard report.