Soundhound Ai Ip, LLC

Soundhound, Inc.

Other

Karl Stahl

Philipp Hubert

Bernard Mont-reynaud

Irina A Spiridonova

Katayoun Norouzi

Mara Selvaggi

Utku Yabas

Methods and systems for pre-wakeword speech processing are disclosed. Speech audio, comprising command speech spoken before a wakeword, may be stored in a buffer in oldest to newest order. Upon detection of the wakeword, reverse acoustic models and language models, such as reverse automatic speech recognition (R-ASR) can be applied to the buffered audio, in newest to oldest order, starting from before the wakeword. The speech is converted into a sequence of words. Natural language grammar models, such as natural language understanding (NLU), can be applied to match the sequence of words to a complete command, the complete command being associated with invoking a computer operation.

Pre-wakeword speech processing with reverse automatic speech recognition

[Object] Technology is provided to enable a mobile terminal to function as a digital assistant even when the mobile terminal is in a state where it cannot communicate with a server apparatus. [Solution] When a user terminalreceives a query A from a user, user terminalsends query A to a server. Serverinterprets the meaning of query A using a grammar A. Serverobtains a response to query A based on the meaning of query A and sends the response to user terminal. Serverfurther sends grammar A to user terminal. That is, serversends to user terminala grammar used to interpret the query received from user terminal

Automatic synchronization for an offline virtual assistant

A user specifies a natural language command to a device. Software on the device generates contextual metadata about the user interface of the device, such as data about all visible elements of the user interface, and sends the contextual metadata along with the natural language command to a natural language understanding engine. The natural language understanding engine parses the natural language query using a stored grammar (e.g., a grammar provided by a maker of the device) and as a result of the parsing identifies information about the command (e.g., the user interface elements referenced by the command) and provides that information to the device. The device uses that provided information to respond to the command.

Enabling natural language interactions with user interfaces for users of a software application

A voice-controlled device includes a microphone to receive a set of sound waves that includes speech uttered by a user and other sound, and to output a first audio signal that includes a contribution from the speech uttered by the user and a contribution from the other sound. The device also includes a receiver to receive an electromagnetic signal and to output a second audio signal obtained from the electromagnetic signal. An audio pre-processor of the device processes the first audio signal using the second audio signal to reduce the contribution from the other sound in a processed audio signal. The voice-controlled device then provides the processed audio signal to a speech recognition module to determine a voice command issued by the user.

Multi-modal audio processing for voice-controlled devices

A speaker device includes an electroacoustic transducer configured to convert an audio signal into a set of sound waves and a transmitter configured to transmit an electromagnetic signal that carries the audio signal for receipt at distances limited to an audibility range of the set of sound waves. The audibility range of the set of sound waves corresponds to a distance at which the set of sound waves is estimated to be below a predetermined sound level.

Loudspeaker with transmitter

The technology disclosed relates to retrieving a personal memo from a database. The method includes receiving, by a virtual assistant, a natural language utterance that expresses a request, interpreting the natural language utterance according to a natural language grammar rule for retrieving memo data from the natural language utterance, the natural language grammar rule recognizing query information, responsive to interpreting the natural language utterance, using the query information to query the database for a memo related to the query information, and providing, to a user, a response generated in dependence upon the memo related to the query information.

Using a virtual assistant to store a personal voice memo and to obtain a response based on a stored personal voice memo that is retrieved according to a received query

A system and method are disclosed for capturing a segment of speech audio, performing phoneme recognition on the segment of speech audio to produce a segmented phoneme sequence, comparing the segmented phoneme sequence to stored phoneme sequences that represent incorrect pronunciations of words to determine if there is a match, and identifying an incorrect pronunciation for a word in the segment of speech audio. The system builds a library based on the data collected for the incorrect pronunciations.

System and method for detection and correction of incorrectly pronounced words

Either or both of voice speaker identification or utterance classification such as by age, gender, accent, mood, and prosody characterize speech utterances in a system that performs automatic speech recognition (ASR) and natural language processing (NLP). The characterization conditions NLP, either through application to interpretation hypotheses or to specific grammar rules. The characterization also conditions language models of ASR. Conditioning may comprise enablement and may comprise reweighting of hypotheses.

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Menlo Park, CA, United States of America

Karl Stahl