PATENT CLAIM ANALYSIS

Application Number: 15871836
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-05
Patent Classification: ["704", "235000"]

Abstract:
A speech recognition system for resolving impaired utterances can have a speech recognition engine configured to receive a plurality of representations of an utterance and concurrently to determine a plurality of highest-likelihood transcription candidates corresponding to each respective representation of the utterance. The recognition system can also have a selector configured to determine a most-likely accurate transcription from among the transcription candidates. As but one example, the plurality of representations of the utterance can be acquired by a microphone array, and beamforming techniques can generate independent streams of the utterance across various look directions using output from the microphone array.

Claim (Index 1):
A speech recognition system for resolving impaired utterances, comprising:\n a speech recognition engine configured to receive a plurality of representations of an utterance and concurrently to determine a plurality of highest-likelihood transcription candidates corresponding to each respective representation of the utterance; and a selector configured to determine a most-likely accurate transcription from among the plurality of highest-probability transcription.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 86.0
- Lexical Diversity: 1.75
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14732715', '14732711', '15703033', '14532208', '12240172']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.296820310385039
- 35 USC 102 Novelty (BERT): 0.516005198622443
- Combined Prediction Score: 0.3187387992087794
- Mean Citation Score: 248.040494
- Max Citation Score: 349.62708
- Similarity Product: 327.700782455492

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

Dataset: test