Abstract:
Methods and systems are provided for shaping speech dialog of a speech system. In one embodiment, a method includes: receiving data related to a first utterance from a user of the speech system; processing the data based on at least one attribute processing technique that determines at least one attribute of the first utterance; determining a shaping pattern based on the at least one attribute; and generating a speech prompt based on the shaping pattern.
Abstract:
A system for context-based adaptive virtual experience control in a vehicle is provided. The system includes an output device configured for providing a sensory output to a user of the vehicle and a computerized virtual experience control module configured for controlling the output device based upon a virtual experience mode. The system further includes a computerized context-based adaptive control module configured for monitoring contextual data related to one of the user of the vehicle or operation of the vehicle, monitoring feedback from the user related to one of favor or disfavor related to the virtual experience mode, and utilizing the contextual data and the feedback from the user to selectively, automatically command activation of the virtual experience mode.
Abstract:
Methods and systems are provided for adapting a speech system. In one example a method includes: processing a spoken command with one or more models of one or more model types to achieve model results; evaluating a frequency of the model results; and selectively updating the one or more models of the one or more model types based on the evaluating.
Abstract:
Methods and systems are provided for adapting a speech system. In one example a method includes: logging speech data from the speech system; processing the speech data for a pattern of a user competence associated with at least one of task requests and interaction behavior; and selectively updating at least one of a system prompt and an interaction sequence based on the user competence.
Abstract:
A method of loading content items for accessibility by a vehicle automatic speech recognition (ASR) system. The method tracks content items requested by one or more users and prioritizes the loading of requested content items and/or selectively loads requested content items at least partially based on the interaction history of one or more users. The method may also adapt the ASR system based on the interaction history of one or more users to make preferred content items readily accessible instead of randomly accessible.
Abstract:
A system and method of adapting a speech system includes the steps of: receiving confirmation of a phonetic transcription of one or more names, receiving confirmation of a selected stored text result, and storing the phonetic transcription with the selected stored text result using an automatic speech recognition (ASR) system, a text-to-speech (TTS) system, or both.
Abstract:
A method and system can control a speech recognition system in a vehicle. The method includes monitoring adaptive feature data about interactions between a user and the speech recognition system. The method includes determining a first group of samples of the adaptive feature data and creating a control chart based on the first group of samples. The control chart includes a control limit. The method further includes determining a second group of samples of the adaptive feature data after creating the control chart. Furthermore, the method includes calculating an arithmetic mean of each sample of the second group of samples to determine a sample mean, comparing the sample mean to the control limit in order identify unexpected performance of the speech recognition system. The method includes adjusting the speech recognition system based on the identified unexpected performance if the unexpected performance is identified.
Abstract:
Examples of techniques text-to-speech pre-processing for speech recognition and speech synthesis are disclosed. In one example implementation, a computer-implemented method includes receiving, by a processing device, an automated speech recognition output comprising an n-best list and associated confidence scores. The method further includes performing, by the processing device, a TTS pre-processing on the n-best list and associated confidence scores to generate a read back message, wherein the read back message comprises a read back instruction. The method further includes sending, by the processing device, the read back message to a TTS speech synthesizer for generating an audible signal based on the read back message to cause an audio device to present the read back message.
Abstract:
Examples of techniques text-to-speech pre-processing for speech recognition and speech synthesis are disclosed. In one example implementation, a computer-implemented method includes receiving, by a processing device, an automated speech recognition output comprising an n-best list and associated confidence scores. The method further includes performing, by the processing device, a TTS pre-processing on the n-best list and associated confidence scores to generate a read back message, wherein the read back message comprises a read back instruction. The method further includes sending, by the processing device, the read back message to a TTS speech synthesizer for generating an audible signal based on the read back message to cause an audio device to present the read back message.
Abstract:
Methods and systems are provided for adapting a speech system. In one example a method includes: logging speech data from the speech system; detecting a user characteristic from the speech data; and selectively updating a language model based on the user characteristic.