A voice system of a moving machine is a voice system of a moving machine driven by a driver who is exposed to an outside of the moving machine and includes: a noise estimating section which estimates a future noise state based on information related to a noise generation factor; and a voice control section which changes an attribute of voice in accordance with the estimated noise state, the voice being voice to be output to the driver.

In one aspect, a device may include at least one processor and storage accessible to the at least one processor. The storage includes instructions executable by the at least one processor to correlate a first trigger phrase for a digital assistant to a name of a person within a proximity to the device and/or a topic of discussion. Based on the correlation, the instructions are executable to set the digital assistant to decline to monitor for utterance of the first trigger phrase and instead monitor for utterance of a second trigger phrase that is different from the first trigger phrase.

In one aspect, a device may include at least one processor and storage accessible to the at least one processor. The storage includes instructions executable by the at least one processor to correlate a first trigger phrase for a digital assistant to a name of a person within a proximity to the device and/or a topic of discussion. Based on the correlation, the instructions are executable to set the digital assistant to decline to monitor for utterance of the first trigger phrase and instead monitor for utterance of a second trigger phrase that is different from the first trigger phrase.

A method may include obtaining first audio data originating at a first device during a communication session between the first device and a second device. The method may also include obtaining a first text string that is a transcription of the first audio data, where the first text string may be generated using automatic speech recognition technology using the first audio data. The method may also include obtaining a second text string that is a transcription of second audio data, where the second audio data may include a revoicing of the first audio data by a captioning assistant and the second text string may be generated by the automatic speech recognition technology using the second audio data. The method may further include generating an output text string from the first text string and the second text string and using the output text string as a transcription of the speech.

A method may include obtaining first audio data originating at a first device during a communication session between the first device and a second device. The method may also include obtaining a first text string that is a transcription of the first audio data, where the first text string may be generated using automatic speech recognition technology using the first audio data. The method may also include obtaining a second text string that is a transcription of second audio data, where the second audio data may include a revoicing of the first audio data by a captioning assistant and the second text string may be generated by the automatic speech recognition technology using the second audio data. The method may further include generating an output text string from the first text string and the second text string and using the output text string as a transcription of the speech.

A symbol prediction method includes storing a statistic for each of a set of symbols w in at least one context, each context including a string of k preceding symbols and a string of l subsequent symbols, the statistic being based on observations of a string kwl in training data. For an input sequence of symbols, a prediction is computed for at least one symbol in the input sequence, based on the stored statistics. The computing includes, where the symbol is in a context in the sequence not having a stored statistic, computing the prediction for the symbol in that context based on a stored statistic for the symbol in a more general context.

A symbol prediction method includes storing a statistic for each of a set of symbols w in at least one context, each context including a string of k preceding symbols and a string of l subsequent symbols, the statistic being based on observations of a string kwl in training data. For an input sequence of symbols, a prediction is computed for at least one symbol in the input sequence, based on the stored statistics. The computing includes, where the symbol is in a context in the sequence not having a stored statistic, computing the prediction for the symbol in that context based on a stored statistic for the symbol in a more general context.

In an approach for optimizing an intelligent virtual assistant by using phonetic comparison to find a response stored in a local database, a processor receives an audio input on a computing device. A processor transcribes the audio input to text. A processor compares the text to a set of user queries and commands in a local database of the computing device using a phonetic algorithm. A processor determines whether a user query or command of the set of user queries and commands meets a pre-defined threshold of similarity. Responsive to determining that the user query or command meets the pre-defined threshold of similarity, a processor identifies an intention of a set of intentions stored in the local database corresponding to the user query or command. A processor identifies a response of a set of responses in the local database corresponding to the intention. A processor outputs the response audibly.

In an approach for optimizing an intelligent virtual assistant by using phonetic comparison to find a response stored in a local database, a processor receives an audio input on a computing device. A processor transcribes the audio input to text. A processor compares the text to a set of user queries and commands in a local database of the computing device using a phonetic algorithm. A processor determines whether a user query or command of the set of user queries and commands meets a pre-defined threshold of similarity. Responsive to determining that the user query or command meets the pre-defined threshold of similarity, a processor identifies an intention of a set of intentions stored in the local database corresponding to the user query or command. A processor identifies a response of a set of responses in the local database corresponding to the intention. A processor outputs the response audibly.

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.