| CPC G10L 15/22 (2013.01) [G10L 15/26 (2013.01); G06Q 30/0635 (2013.01); G06Q 50/12 (2013.01); G10L 2015/227 (2013.01)] | 10 Claims |

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1. A method, comprising:
engaging a consumer in a natural language voice dialogue to place an order at an establishment using voice characteristics specific to the consumer and a lexicon specific to ordering with the establishment;
translating speech of the consumer into text based on the voice characteristics that are specific to the consumer and the lexicon associated with ordering, wherein the translating utilizes a machine learning algorithm that receives as input the voice characteristics, an audio snippet of consumer speech, and the lexicon, and provides as output the text that corresponds to the speech;
customizing voice interaction using deep learning techniques by performing an initial voice training session to capture voice features and characteristics for the consumer;
wherein during the initial voice training session:
displaying text sentences on a display device;
receiving audio snippets of the speech from the consumer in response to prompts to the consumer to repeat the text sentences; and
training the machine learning algorithm to return voice features of the consumer, wherein corresponding features are retained in a voice profile specific to the consumer; and
training a non-user specific machine learning algorithm to utilize the voice profile to enable text translation for the consumer;
placing the order within an order system associated with the establishment using menu options obtained from the consumer during the engaging; and
sending a message to a fulfillment terminal of the establishment to begin order preparation when location data associated with a consumer device of the consumer indicates that the consumer is in route to the establishment to pick up the order and a calculated time in which the consumer is estimated to arrive at the establishment, wherein the calculated time corresponds with an order preparation time for the establishment to complete the order.
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