PATENT CLAIM ANALYSIS

Application Number: 15763642
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-11
Patent Classification: ["379", "067100"]

Abstract:
An enterprise voice system such as a contact centre is disclosed which provides a speech analytics capability. Whilst call recording is common in many contact centres, calls are normally recorded in single-channel audio files in order to save costs. Previous attempts to provide automatic diarization of those recorded calls have relied on training the system to recognise voiceprints of users of the system, and then comparing utterances within the recorded calls to those voiceprints in order to identify who was speaking at that time. In order to avoid the need to train the system to recognise voiceprints, an enterprise voice system is disclosed which inserts a digital watermark into the digitised audio signal from each user's microphone. By inserting the digital watermark with an energy, and, in some cases also with a spectrum, which matches the digitised audio signal, and taking advantage of typically only one user speaking at a time, a mark is left in the recorded call which a speech analytics system can use in order to identify who was speaking at different times in the conversation.

Claim (Index 2):
A method according to  claim 1  wherein said speaker-dependent signal is generated from a predetermined speaker identification signal.

Metadata:
- Claim Count in Document: 28.0
- Percentile: 90.0
- Lexical Diversity: 1.93
- Patent Class: 379.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['14605915', '15876534', '13494771', '10370440', '12925618']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5402422564249646
- 35 USC 102 Novelty (BERT): 0.4732330074597584
- Combined Prediction Score: 0.5335413315284441
- Mean Citation Score: 166.83054800000005
- Max Citation Score: 172.67014
- Similarity Product: 121.37725030359628

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