PATENT CLAIM ANALYSIS

Application Number: 16146416
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-02
Patent Classification: ["704", "232000"]

Abstract:
Techniques are provided for efficient acoustic event detection with reduced resource consumption. A methodology implementing the techniques according to an embodiment includes calculating frames of power spectra based on segments of received acoustic signals. The method further includes two processes, one for detecting impulsive acoustic events and another for detecting continuous acoustic events. The first process includes generating impulsive acoustic event features associated with first and second power spectrum frames, applying a neural network classifier to the impulsive acoustic event features to generate event scores, and detecting an impulsive acoustic event based on those event scores. The second process includes generating reduced-dimension continuous acoustic event features associated with the first and second power spectrum frames, applying a neural network classifier to the reduced-dimension continuous acoustic event features to generate a second set of event scores, and detecting a continuous acoustic event based on the second set of event scores.

Claim (Index 3):
The method of  claim 1 , wherein the generating of the reduced-dimension continuous acoustic event features comprises:\n applying a non-linear filter bank to the frames of the acoustic signal to distribute the acoustic signal over non-linearly spaced frequency bins; performing a Discrete Cosine Transform (DCT) on the non-linearly spaced frequency bins; calculating a logarithm of the DCT transformed bins to generate Mel-Frequency Cepstral Coefficients (MFCCs); and performing dimensionality reduction on the MFCCs to generate the reduced-dimension continuous acoustic event features.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 97.0
- Lexical Diversity: 2.52381
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['13796670', '15910387', '14268459', '15583012', '15494193']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2757689135361422
- 35 USC 102 Novelty (BERT): 0.466815455341332
- Combined Prediction Score: 0.2948735677166612
- Mean Citation Score: 134.93855000000002
- Max Citation Score: 148.62807
- Similarity Product: 110.52632805865824

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

Dataset: test