Abstract: A method of generating text from speech using video-speech matching from a primary user is disclosed herein. The method requires first receiving a video and audio input. The video and audio inputs are then segmented into a plurality of video and audio features, respectively. The plurality of video and audio features are then matched according to their similarities. A primary speaker is then determined from one of the matched video and audio features. The primary speaker's matched video and audio features are then used to generate a text representative of the primary speaker's speech.

Abstract: An improved speech-based/natural language point-of-sale customer order system which is useful for any business that interacts with customers through speech or sound. Despite the advances in speech recognition, currently available voice ordering interfaces have proven to be unintuitive and lack reliability. Voice recognition has so far proven to be inefficient in retail contexts, and therefore voice recognition has so far achieved a low level of usage penetration in the retail sector. The present invention facilitates the automated operation of the ordering function of a drive-through restaurant, fast food restaurant or other business establishment by replacing an employee or other means of capturing order data with an ordering system employing a highly accurate speech recognition component that is able to be trained to recognize a wide vocabulary of words, and associate tones and other metadata in a manner not previously achieved in speech-to-text systems.

Abstract: A method of generating text from speech using video-speech matching from a primary user is disclosed herein. The method requires first receiving a video and audio input. The video and audio inputs are then segmented into a plurality of video and audio features, respectively. The plurality of video and audio features are then matched according to their similarities. A primary speaker is then determined from one of the matched video and audio features. The primary speaker's matched video and audio features are then used to generate a text representative of the primary speaker's speech.

Abstract: An improved speech-based/natural language point-of-sale customer order system which is useful for any business that interacts with customers through speech or sound. Despite the advances in speech recognition, currently available voice ordering interfaces have proven to be unintuitive and lack reliability. Voice recognition has so far proven to be inefficient in retail contexts, and therefore voice recognition has so far achieved a low level of usage penetration in the retail sector. The present invention facilitates the automated operation of the ordering function of a drive-through restaurant, fast food restaurant or other business establishment by replacing an employee or other means of capturing order data with an ordering system employing a highly accurate speech recognition component that is able to be trained to recognize a wide vocabulary of words, and associate tones and other metadata in a manner not previously achieved in speech-to-text systems.