Systems and methods for a media guidance application that generates results in multiple languages for search queries. In particular, the media guidance application resolves multiple language barriers by taking automatic and manual user language settings and applying those settings to a variety of potential search results.

Systems and methods for presenting inference models based on interrelationships among inference models are provided. For example, information related to a group of at least three inference models may be obtained. Further, in some examples, a plurality of interrelationship records may be obtained, wherein each interrelationship record may correspond to one subgroup of the group of at least three inference models, and each subgroup may comprise at least two inference models. Further, in some examples, the plurality of interrelationship records may be used to determine information related to a first inference model of the group of at least three inference models. Further, in some examples, the determined information may be used to present the first inference model to a user.

Systems and methods for presenting inference models based on interrelationships among inference models are provided. For example, information related to a group of at least three inference models may be obtained. Further, in some examples, a plurality of interrelationship records may be obtained, wherein each interrelationship record may correspond to one subgroup of the group of at least three inference models, and each subgroup may comprise at least two inference models. Further, in some examples, the plurality of interrelationship records may be used to determine information related to a first inference model of the group of at least three inference models. Further, in some examples, the determined information may be used to present the first inference model to a user.

A video is received. One or more subtitles are determined for the video. Whether a word found in a background of the video is similar to a word found in the one or more subtitles is determined. Responsive to determining the word found in the background of the video is similar to the word found in the one or more subtitles, one or more updated subtitles are generated. The one or more updated subtitles include the word found in the background of the video and remove the word found in the one or more subtitles that is similar. A metric for the one or more updated subtitles is calculated. Whether the metric is larger than a threshold is determined. Responsive to determining the metric is larger than the threshold, the video is updated to include the one or more updated subtitles.

A method for automatic hotword threshold tuning includes receiving, from a user device executing a first stage hotword detector configured to detect a hotword in streaming audio, audio data characterizing the detected hotword. The method includes processing, using a second stage hotword detector, the audio data to determine whether the hotword is detected by the second stage hotword detector. When the hotword is not detected, the method includes identifying a false acceptance instance at the first stage hotword detector indicating that the first stage hotword detector incorrectly detected the hotword. The method includes determining whether a false acceptance rate satisfies a false acceptance rate threshold based on a number of false acceptance instances within a false acceptance time period. When the false acceptance rate satisfies the false acceptance rate threshold, the method includes adjusting the hotword detection threshold of the first stage hotword detector.

A method for automatic hotword threshold tuning includes receiving, from a user device executing a first stage hotword detector configured to detect a hotword in streaming audio, audio data characterizing the detected hotword. The method includes processing, using a second stage hotword detector, the audio data to determine whether the hotword is detected by the second stage hotword detector. When the hotword is not detected, the method includes identifying a false acceptance instance at the first stage hotword detector indicating that the first stage hotword detector incorrectly detected the hotword. The method includes determining whether a false acceptance rate satisfies a false acceptance rate threshold based on a number of false acceptance instances within a false acceptance time period. When the false acceptance rate satisfies the false acceptance rate threshold, the method includes adjusting the hotword detection threshold of the first stage hotword detector.

Methods and systems for dynamically updating machine learning models that provide conversational responses through the use of a configuration file that defines modifications and changes to the machine learning model are disclosed. For example, the configuration file may be used to define an expected behavior and required attributes for instituting modifications and changes (e.g., via a mutation algorithm) to the machine learning model.

Methods and systems for dynamically updating machine learning models that provide conversational responses through the use of a configuration file that defines modifications and changes to the machine learning model are disclosed. For example, the configuration file may be used to define an expected behavior and required attributes for instituting modifications and changes (e.g., via a mutation algorithm) to the machine learning model.

A system and method is provided for combining active and unsupervised learning for automatic speech recognition. This process enables a reduction in the amount of human supervision required for training acoustic and language models and an increase in the performance given the transcribed and un-transcribed data.

A system and method is provided for combining active and unsupervised learning for automatic speech recognition. This process enables a reduction in the amount of human supervision required for training acoustic and language models and an increase in the performance given the transcribed and un-transcribed data.