System and method for natural language processing
First Claim
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1. A method for natural language processing, implementable by a server, the method comprising:
- obtaining, from a computing device, an audio input and a current interface, wherein the current interface is associated with a context comprising a first context and a second context; and
determining a query associated with the audio input based on the audio input and the context of the current interface by;
feeding the audio input to a voice recognition engine to determine raw texts corresponding to the audio input;
adjusting a weight in one or more first machine learning models based on the first context associated with the current interface;
applying the one or more first machine learning models to the first context and to;
the raw texts, pre-processed texts, tokenized texts, or vectorized texts, to obtain an intent classification of the audio input according to the weight, wherein the pre-processed texts, tokenized texts, and vectorized texts are associated with the raw texts;
applying one or more second machine learning models to the second context and to;
the raw texts, the pre-processed texts, the tokenized texts, or the vectorized texts to obtain one or more sub-classification prediction distributions of the audio input;
comparing the one or more sub-classification prediction distributions with a preset threshold and against an intent database to obtain an intent sub-classification of the audio input, wherein the intent sub-classification corresponds to a sub-classification prediction distribution exceeding the preset threshold and matches an intent in the intent database; and
determining the query based on the intent classification or the intent sub-classification of the audio input.
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Abstract
Systems and methods are provided for natural language processing. An exemplary method implementable by a server may comprise: obtaining, from a computing device, an audio input and a current interface, wherein the current interface is associated with a context; and determining a query associated with the audio input based at least on the audio input and the context of the current interface.
22 Citations
20 Claims
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1. A method for natural language processing, implementable by a server, the method comprising:
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obtaining, from a computing device, an audio input and a current interface, wherein the current interface is associated with a context comprising a first context and a second context; and determining a query associated with the audio input based on the audio input and the context of the current interface by; feeding the audio input to a voice recognition engine to determine raw texts corresponding to the audio input; adjusting a weight in one or more first machine learning models based on the first context associated with the current interface; applying the one or more first machine learning models to the first context and to;
the raw texts, pre-processed texts, tokenized texts, or vectorized texts, to obtain an intent classification of the audio input according to the weight, wherein the pre-processed texts, tokenized texts, and vectorized texts are associated with the raw texts;applying one or more second machine learning models to the second context and to;
the raw texts, the pre-processed texts, the tokenized texts, or the vectorized texts to obtain one or more sub-classification prediction distributions of the audio input;comparing the one or more sub-classification prediction distributions with a preset threshold and against an intent database to obtain an intent sub-classification of the audio input, wherein the intent sub-classification corresponds to a sub-classification prediction distribution exceeding the preset threshold and matches an intent in the intent database; and determining the query based on the intent classification or the intent sub-classification of the audio input. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system for natural language processing, implementable on a server, comprising a processor and a non-transitory computer-readable storage medium storing instructions that, when executed by the processor, cause the system to perform a method, the method comprising:
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obtaining, from a computing device, an audio input and a current interface, wherein the current interface is associated with a context comprising a first context and a second context; and determining a query associated with the audio input based on the audio input and the context of the current interface by; feeding the audio input to a voice recognition engine to determine raw texts corresponding to the audio input; adjusting a weight in one or more first machine learning models based on the first context associated with the current interface; applying the one or more first machine learning models to the first context and to;
the raw texts, pre-processed texts, tokenized texts, or vectorized texts, to obtain an intent classification of the audio input, wherein the pre-processed texts, tokenized texts, and vectorized texts are associated with the raw texts;applying one or more second machine learning models to the second context and to;
the raw texts, the pre-processed texts, the tokenized texts, or the vectorized texts to obtain one or more sub-classification prediction distributions of the audio input;comparing the one or more sub-classification prediction distributions with a preset threshold and against an intent database to obtain an intent sub-classification of the audio input, wherein the intent sub-classification corresponds to a sub-classification prediction distribution exceeding the preset threshold and matches an intent in the intent database; and determining the query based on the intent classification or the intent sub-classification of the audio input. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A method for natural language processing, comprising:
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obtaining an audio input from a computing device, wherein the audio is inputted to the computing device when a first interface of the computing device is active; determining a context of the first interface, the first interface comprising an interface associated with media, an interface associated with navigation, or an interface associated with messaging, the context comprising a first context and a second context; feeding the audio input and the context of the first interface to one or more algorithms to determine an audio instruction associated with the audio input; and transmitting a computing device instruction to the computing device based on the determined audio instruction, causing the computing device to execute the computing device instruction, wherein feeding the audio input and the context of the first interface to one or more algorithms to determine an audio instruction associated with the audio input comprises; feeding the audio input to a voice recognition engine to determine raw texts corresponding to the audio input; adjusting a weight in one or more first machine learning models based on the first context associated with the current interface; and applying the one or more first machine learning models to the first context and to; the raw texts, pre-processed texts, tokenized texts, or vectorized texts, to obtain an intent classification of the audio input, wherein the pre-processed texts, tokenized texts, and vectorized texts are associated with the raw texts; applying one or more second machine learning models to the second context and to;
the raw texts, the pre-processed texts, the tokenized texts, or the vectorized texts to obtain one or more sub-classification prediction distributions of the audio input;comparing the one or more sub-classification prediction distributions with a preset threshold and against an intent database to obtain an intent sub-classification of the audio input, wherein the intent sub-classification corresponds to a sub-classification prediction distribution exceeding the preset threshold and matches an intent in the intent database. - View Dependent Claims (20)
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Specification