PATENT CLAIM ANALYSIS

Application Number: 16240928
Application Type: Utility
Filing Date: 2019-01
Publication Date: 2019-05
Patent Classification: ["704", "232000"]

Abstract:
Symbol sequences are estimated using a computer-implemented method including detecting one or more candidates of a target symbol sequence from a speech-to-text data, extracting a related portion of each candidate from the speech-to-text data, detecting repetition of at least a partial sequence of each candidate within the related portion of the corresponding candidate, labeling the detected repetition with a repetition indication, and estimating whether each candidate is the target symbol sequence, using the corresponding related portion including the repetition indication of each of the candidates.

Claim (Index 14):
An apparatus comprising:\n a processor; and one or more computer readable mediums collectively including instructions that, when executed by the processor, cause the processor to perform operations comprising: detecting repetitions of at least a partial sequence of related portions of one or more candidates of a target symbol sequence from a speech-to-text data, and labeling the detected repetitions with a repetition indication, estimating, by employing a trained estimation model with a plurality of Long Short-Term Memory (LSTM) neural networks, whether each candidate is the target symbol sequence, based on the corresponding related portion including the repetition indication of each of the candidates, wherein each candidate is divided into a plurality of word groups, with each of a plurality of word groups being fed into one of a plurality of LSTM neural networks to generate a plurality of outputs, with the plurality of outputs being fed into a softmax layer.

Metadata:
- Claim Count in Document: 65.0
- Percentile: 99.0
- Lexical Diversity: 2.11628
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15409126', '11427954', '14090761', '15243838', '10950074']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2230430382219264
- 35 USC 102 Novelty (BERT): 0.5661166518018386
- Combined Prediction Score: 0.2573503995799176
- Mean Citation Score: 216.71397400000004
- Max Citation Score: 434.35645
- Similarity Product: 400.73957837111055

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

Dataset: test