PATENT CLAIM ANALYSIS

Application Number: 16170278
Application Type: Utility
Filing Date: 2018-10
Publication Date: 2019-02
Patent Classification: ["704", "235000"]

Abstract:
Systems and methods of diarization using linguistic labeling include receiving a set of diarized textual transcripts. A least one heuristic is automatedly applied to the diarized textual transcripts to select transcripts likely to be associated with an identified group of speakers. The selected transcripts are analyzed to create at least one linguistic model. The linguistic model is applied to transcripted audio data to label a portion of the transcripted audio data as having been spoken by the identified group of speakers. Still further embodiments of diarization using linguistic labeling may serve to label agent speech and customer speech in a recorded and transcripted customer service interaction.

Claim (Index 21):
A method of diarization, the method comprising:\n receiving a set of textual transcripts from a transcription server and a set of audio files associated with the set of textual transcripts from an audio database server; performing a blind diarization on the set of textual transcripts and the set of audio files to segment and cluster the textual transcripts into a plurality of textual speaker clusters, wherein the number of textual speaker clusters is at least equal to a number of speakers in the textual transcript; automatedly applying at least one heuristic to the textual speaker clusters with a processor to select textual speaker clusters likely to be associated with an identified group of speakers; analyzing the selected textual speaker clusters with the processor to create at least one linguistic model; applying the linguistic model to transcribed audio data with the processor to label a portion of the transcribed audio data as having been spoken by the identified group of speakers; saving the at least one linguistic model to a linguistic database server and associating it with the labeled speaker; and with the processor, applying the saved at least one linguistic model from the linguistic database server to a new audio file transcript from an audio source to perform diarization of the new audio file by blind diarizing the new audio file, comparing each new textual speaker cluster to the at least one linguistic model, and labeling each textual speaker cluster as belonging to a customer service agent or belonging to a customer.

Metadata:
- Claim Count in Document: 32.0
- Percentile: 97.0
- Lexical Diversity: 1.7619
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14084976', '16170297', '16170289', '14084974', '15254326']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3553224047849923
- 35 USC 102 Novelty (BERT): 0.609789996961239
- Combined Prediction Score: 0.3807691640026169
- Mean Citation Score: 453.5134440000001
- Max Citation Score: 540.5999
- Similarity Product: 534.6465465399207

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