PATENT CLAIM ANALYSIS

Application Number: 16403281
Application Type: Utility
Filing Date: 2019-05
Publication Date: 2019-08
Patent Classification: ["704", "002000"]

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a target sequence from an input sequence. In one aspect, a method comprises maintaining a set of current hypotheses, wherein each current hypothesis comprises an input prefix and an output prefix. For each possible combination of input and output prefix length, the method extends any current hypothesis that could reach the possible combination to generate respective extended hypotheses for each such current hypothesis; determines a respective direct score for each extended hypothesis using a direct model; determines a first number of highest-scoring hypotheses according to the direct scores; rescores the first number of highest-scoring hypotheses using a noisy channel model to generate a reduced number of hypotheses; and adds the reduced number of hypotheses to the set of current hypotheses.

Claim (Index 12):
One or more non-transitory computer storage media encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:\n maintaining a set of current hypotheses, wherein each current hypothesis comprises an input prefix covering a respective first number i inputs in the input sequence and a target prefix of respective length j, and wherein each current hypothesis has a respective model score; and for each of a plurality of possible combinations of number of inputs i and output prefix length j:\n iteratively extending one or more current hypotheses from the set of current hypotheses to reach the possible combination by: \n i) for each of the one or more current hypotheses, extending the target prefix of the current hypothesis by one target token and either not extending the input prefix or extending the input prefix by one or more input tokens, to generate an iteratively extended hypothesis for the current hypothesis; and \n ii) determining a respective direct score for each iteratively extended hypothesis using a direct model; \n iii) determining a first number of highest-scoring hypotheses of the iteratively extended hypotheses according to the direct scores; \n iv) rescoring the first number of highest-scoring hypotheses of the iteratively extended hypotheses using a noisy channel model to generate a reduced number of hypotheses; and \n v) adding the reduced number of hypotheses to the set of current hypotheses and associating each with the corresponding score generated by the rescoring; wherein the input sequence comprises a sequence of words in an input language, and the target sequence comprises a translation of the sequence of words to a target language.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 100.0
- Lexical Diversity: 2.22388
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['13194972', '14156788', '12477582', '14606706', '11431393']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2627973339868832
- 35 USC 102 Novelty (BERT): 0.4889575163285738
- Combined Prediction Score: 0.2854133522210523
- Mean Citation Score: 194.301084
- Max Citation Score: 206.35846
- Similarity Product: 141.13396248447182

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test