US 12,456,467 B2
Emotion-based voice controlled device
Newton Howard, Potomac, MD (US); and Mustak Ibn Ayub, Oxford (GB)
Filed by Newton Howard, Potomac, MD (US); and Mustak Ibn Ayub, Oxford (GB)
Filed on Aug. 14, 2023, as Appl. No. 18/449,172.
Application 18/449,172 is a continuation of application No. 17/571,860, filed on Jan. 10, 2022, granted, now 11,727,938.
Application 17/571,860 is a continuation of application No. 16/558,627, filed on Sep. 3, 2019, granted, now 11,257,500, issued on Feb. 22, 2022.
Claims priority of provisional application 62/726,672, filed on Sep. 4, 2018.
Prior Publication US 2023/0386474 A1, Nov. 30, 2023
Int. Cl. G10L 25/63 (2013.01); G06F 40/242 (2020.01); G06F 40/30 (2020.01); G10L 15/22 (2006.01); G10L 15/26 (2006.01); G10L 15/32 (2013.01); G06F 16/2457 (2019.01); G06F 16/9535 (2019.01); G06F 40/279 (2020.01); G06F 40/295 (2020.01); G10L 15/18 (2013.01); G10L 15/183 (2013.01); G10L 15/24 (2013.01)
CPC G10L 15/32 (2013.01) [G06F 40/242 (2020.01); G10L 15/22 (2013.01); G10L 15/26 (2013.01); G10L 25/63 (2013.01); G06F 16/2457 (2019.01); G06F 16/24578 (2019.01); G06F 16/9535 (2019.01); G06F 40/279 (2020.01); G06F 40/295 (2020.01); G10L 15/1807 (2013.01); G10L 15/183 (2013.01); G10L 2015/223 (2013.01); G10L 2015/227 (2013.01); G10L 15/24 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving, at a voice controlled device, a voice input from a user, wherein the voice input is in at least one of a plurality of languages;
receiving, at a server computer system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor, the voice input and converting the voice input to text data representing the voice input, wherein the text data includes text data in the at least one of the plurality of languages;
obtaining, at the server computer system, a plurality of items of content responsive to the voice input by searching for content using the text data;
determining, at the server computer system, at least one class related to the voice input;
classifying, at the server computer system, each obtained item of content into at least one class, wherein each obtained item of content is classified into at least one class using text data associated with each item of content by:
counting, at the server computer system, occurrences of words in the text data associated with each item of content, wherein the counted words are included in a dictionary for each class including a ranking of emotional words,
determining, at the server computer system, an apparent number of occurrences of each word in the text data associated with each item of content,
determining, at the server computer system, a contextual weight of each word in the text data associated with each item of content with respect to the item of content,
determining, at the server computer system, a weight of each word in the text data associated with each item of content;
determining, at the server computer system, a score for each class for each item of content based on the counted occurrences of words, the determined apparent number of occurrences of each word, the determined contextual weight of each word, and the determined weight of each word and
classifying, at the server computer system, each item of content into at least one class based on the determined score for each class;
identifying, at the server computer system, at least one item of content classified into at least one class related to the voice input; and
transmitting, at the server computer system, the at least one identified item of content.