Apple USES custom models to identify place names

In a new article in the Machine Learning Journal, apple detailed the challenges of improving Siri's ability to identify local points of interest, such as small businesses and restaurants.

In short, apple says it has built a custom language model, geo-lm, that incorporates users' geo-location knowledge and improves the accuracy of Siri's automated speech recognition system. These models enable Siri to better evaluate users' voice content.

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Apple said it sets the geo-lm system for 169 statistical regions defined by the U.S. Census Bureau, representing 80 percent of the U.S. population. Apple has also set up a separate geo-lm system worldwide to cover all areas that are not covered by statistical regions.

When the user queries Siri, the system USES the geo-lm system based on the user's current location. If the user is not in the statistics area, or Siri has no access to the location service, the system will default to the global geo-lm system.

The apple paper is highly technical and fairly detailed, and hopefully it will help Siri better identify the names of points of interest in different places, and even better differentiate Tom's restaurants in Iowa and Kansas depending on the user's geographic location.

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In testing, the company found that the custom of language model Siri's error rate can be reduced by 41.9% to 48.4%, the error rate distribution in eight major cities in the United States, Boston, Chicago, Los Angeles, Minneapolis, New York, Philadelphia, Seattle and San Francisco, but does not include large chain stores such as wal-mart.

According to a recent study by research firm Loup Ventures, Siri still lags behind Google Assistant in overall accuracy, and it is hoped that these improvements will actually improve Siri's ability to recognize local locations.