Abstract:
The present invention relates to the continuous monitoring of an audio signal and identification of audio items within an audio signal. The technology disclosed utilizes predictive caching of fingerprints to improve efficiency. Fingerprints are cached for tracking an audio signal with known alignment and for watching an audio signal without known alignment, based on already identified fingerprints extracted from the audio signal. Software running on a smart phone or other battery-powered device cooperates with software running on an audio identification server.
Abstract:
The present invention relates to providing identification information in response to an audio segment using a first mode of operation including receiving an audio segment and sending the audio segment to a remote server and receiving, from the remote server, identification information relating to the audio segment, and a second mode of operation of receiving an audio segment and using stored information to obtain identification information relating to the received audio segment received, without sending the audio segment to the remote server. The present invention further includes using identification information from the remote server and using local identification information and selecting either identification information from the remote server or local identification information based on selection criteria, and generating an output based on the selected identification information.
Abstract:
A system and method is presented for performing dual mode speech recognition, employing a local recognition module on a mobile device and a remote recognition engine on a server device. The system accepts a spoken query from a user, and both the local recognition module and the remote recognition engine perform speech recognition operations on the query, returning a transcription and confidence score, subject to a latency cutoff time. If both sources successfully transcribe the query, then the system accepts the result having the higher confidence score. If only one source succeeds, then that result is accepted. In either case, if the remote recognition engine does succeed in transcribing the query, then a client vocabulary is updated if the remote system result includes information not present in the client vocabulary.
Abstract:
A system and method is presented for performing dual mode speech recognition, employing a local recognition module on a mobile device and a remote recognition engine on a server device. The system accepts a spoken query from a user, and both the local recognition module and the remote recognition engine perform speech recognition operations on the query, returning a transcription and confidence score, subject to a latency cutoff time. If both sources successfully transcribe the query, then the system accepts the result having the higher confidence score. If only one source succeeds, then that result is accepted. In either case, if the remote recognition engine does succeed in transcribing the query, then a client vocabulary is updated if the remote system result includes information not present in the client vocabulary.
Abstract:
A method of a local recognition system controlling a host device to perform one or more operations is provided. The method includes receiving, by the local recognition system, a query, performing speech recognition on the received query by implementing, by the local recognition system, a local language context comprising a set of words comprising descriptions in terms of components smaller than the words, and performing speech recognition, using the local language context, to create a transcribed query. Further, the method includes controlling the host device in dependence upon the speech recognition performed on the transcribed query.
Abstract:
A method of a local recognition system controlling a host device to perform one or more operations is provided. The method includes receiving, by the local recognition system, a query, performing speech recognition on the received query by implementing, by the local recognition system, a local language context comprising a set of words comprising descriptions in terms of components smaller than the words, and performing speech recognition, using the local language context, to create a transcribed query. Further, the method includes controlling the host device in dependence upon the speech recognition performed on the transcribed query.
Abstract:
The present invention relates to providing identification information in response to an audio segment using a first mode of operation including receiving an audio segment and sending the audio segment to a remote server and receiving, from the remote server, identification information relating to the audio segment, and a second mode of operation of receiving an audio segment and using stored information to obtain identification information relating to the received audio segment received, without sending the audio segment to the remote server. The present invention further includes using identification information from the remote server and using local identification information and selecting either identification information from the remote server or local identification information based on selection criteria, and generating an output based on the selected identification information.
Abstract:
A system and method is presented for performing dual mode speech recognition, employing a local recognition module on a mobile device and a remote recognition engine on a server device. The system accepts a spoken query from a user, and both the local recognition module and the remote recognition engine perform speech recognition operations on the query, returning a transcription and confidence score, subject to a latency cutoff time. If both sources successfully transcribe the query, then the system accepts the result having the higher confidence score. If only one source succeeds, then that result is accepted. In either case, if the remote recognition engine does succeed in transcribing the query, then a client vocabulary is updated if the remote system result includes information not present in the client vocabulary.