Abstract:
Systems, methods, and computer-readable storage media for intelligent caching of concatenative speech units for use in speech synthesis. A system configured to practice the method can identify, in a local cache of text-to-speech units for a text-to-speech voice an absent text-to-speech unit which is not in the local cache. The system can request from a server the absent text-to-speech unit. The system can then synthesize speech using the text-to-speech units and a received text-to-speech unit from the server.
Abstract:
Systems, methods, and computer-readable storage media for intelligent caching of concatenative speech units for use in speech synthesis. A system configured to practice the method can identify a speech synthesis context, and determine, based on a local cache of text-to-speech units for a text-to-speech voice and based on the speech synthesis context, additional text-to-speech units which are not in the local cache. The system can request from a server the additional text-to-speech units, and store the additional text-to-speech units in the local cache. The system can then synthesize speech using the text-to-speech units and the additional text-to-speech units in the local cache. The system can prune the cache as the context changes, based on availability of local storage, or after synthesizing the speech. The local cache can store a core set of text-to-speech units associated with the text-to-speech voice that cannot be pruned from the local cache.
Abstract:
Disclosed herein are systems, methods, and computer-readable storage media for making a multi-factor decision whether to process speech or language requests via a network-based speech processor or a local speech processor. An example local device configured to practice the method, having a local speech processor, and having access to a remote speech processor, receives a request to process speech. The local device can analyze multi-vector context data associated with the request to identify one of the local speech processor and the remote speech processor as an optimal speech processor. Then the local device can process the speech, in response to the request, using the optimal speech processor. If the optimal speech processor is local, then the local device processes the speech. If the optimal speech processor is remote, the local device passes the request and any supporting data to the remote speech processor and waits for a result.
Abstract:
Systems, methods, and computer-readable storage media for intelligent caching of concatenative speech units for use in speech synthesis. A system configured to practice the method can identify speech units that are required for synthesizing speech. The system can request from a server the text-to-speech unit needed to synthesize the speech. The system can then synthesize speech using text-to-speech units already stored and a received text-to-speech unit from the server.
Abstract:
Disclosed herein are systems, methods, and computer-readable storage devices for fetching speech processing models based on context changes in advance of speech requests using the speech processing models. An example local device configured to practice the method, having a local speech processor, and having access to remote speech models, detects a change in context. The change in context can be based on geographical location, language translation, speech in a different language, user language settings, installing or removing an app, and so forth. The local device can determine a speech processing model that is likely to be needed based on the change in context, and that is not stored on the local device. Independently of an explicit request to process speech, the local device can retrieve, from a remote server, the speech processing model for use on the mobile device.
Abstract:
Systems, methods, and computer-readable storage media for intelligent caching of concatenative speech units for use in speech synthesis. A system configured to practice the method can identify, in a local cache of text-to-speech units for a text-to-speech voice an absent text-to-speech unit which is not in the local cache. The system can request from a server the absent text-to-speech unit. The system can then synthesize speech using the text-to-speech units and a received text-to-speech unit from the server.
Abstract:
Disclosed herein are systems, methods, and computer-readable storage devices for fetching speech processing models based on context changes in advance of speech requests using the speech processing models. An example local device configured to practice the method, having a local speech processor, and having access to remote speech models, detects a change in context. The change in context can be based on geographical location, language translation, speech in a different language, user language settings, installing or removing an app, and so forth. The local device can determine a speech processing model that is likely to be needed based on the change in context, and that is not stored on the local device. Independently of an explicit request to process speech, the local device can retrieve, from a remote server, the speech processing model for use on the mobile device.
Abstract:
Disclosed are systems, methods and computer-readable media for enabling speech processing in a user interface of a device. The method includes receiving an indication of a field and a user interface of a device, the indication also signaling that speech will follow, receiving the speech from the user at the device, the speech being associated with the field, transmitting the speech as a request to public, common network node that receives and processes speech, processing the transmitted speech and returning text associated with the speech to the device and inserting the text into the field. Upon a second indication from the user, the system processes the text in the field as programmed by the user interface. The present disclosure provides a speech mash up application for a user interface of a mobile or desktop device that does not require expensive speech processing technologies.