IP Library Patent Application 18141617
Patent Application
App. No. 18/141,617

SCALABLE AND IN-MEMORY INFORMATION EXTRACTION AND ANALYTICS ON STREAMING RADIO DATA

Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US None
App. No.
18/141,617
Abstract

A method and system for processing an audio stream include receiving an audio stream by a node, splitting the audio stream into segments using a producer-consumer algorithm in the memory of the node, where the audio stream is split into the segments based on silence detection, transcribing voice included in a segment into text using a voice-to-text conversion engine, and performing natural language processing on the text to identify situational insights from the segment.

Claims (46)

1 . A computer-implemented method of processing an audio stream, comprising:

receiving an audio stream by a node;

splitting the audio stream into segments using a producer-consumer algorithm in a memory of the node, the audio stream being split into the segments based on silence detection;

transcribing voice included in a segment into text using a voice-to-text conversion engine; and

performing natural language processing on the text to identify situational insights from the segment.

2 . The computer-implemented method of claim 1 , wherein the audio stream is an HTTP live stream.

3 . The computer-implemented method of claim 1 , wherein splitting the audio stream into segments using a producer-consumer algorithm comprises:

creating a mediator buffer, a producer thread, and a consumer thread in the memory of the node;

enabling the producer thread to process one or more earliest portions of the audio stream as audio blocks and store the audio blocks in the mediator buffer; and

responsive to the mediator buffer being full, enabling the consumer thread to consume the audio blocks in the mediator buffer, wherein consuming the audio blocks comprises splitting each of one or more of the audio blocks into two or more segments, and wherein consuming each audio block in the mediator buffer causes the mediator buffer to have more free space.

4 . The computer-implemented method of claim 3 , further comprising:

responsive to the mediator buffer being emptied by the consumer thread, enabling the producer thread to process one or more updated earliest portions of the audio stream.

5 . The computer-implemented method of claim 3 , wherein a size of the mediator buffer is determined based on a bitrate of the audio stream.

6 . The computer-implemented method of claim 3 , wherein the consumer thread is disabled when the producer thread is enabled to process the one or more earliest portions of the audio stream and store the audio blocks in the mediator buffer.

7 . The computer-implemented method of claim 3 , wherein the producer thread is disabled when the consumer thread is enabled to consume the audio blocks in the mediator buffer.

8 . The computer-implemented method of claim 3 , wherein splitting the audio stream into segments based on silence detection comprises:

detecting a period of silence included in an audio block based on audio waves detected on the audio block;

comparing a time length of the period of silence to a predefined threshold; and

responsive to the time length of the period of silence being larger than the predefined threshold, determining that the period of silence is a place to split the audio block.

9 . The computer-implemented method of claim 8 , wherein detecting a period of silence included in an audio block comprises detecting multiple periods of silence in the audio block.

10 . The computer-implemented method of claim 1 , wherein, before transcribing the voice included in a segment, the method further comprises:

performing a padding process on the split segments

11 . The computer-implemented method of claim 1 , wherein, before transcribing the voice included in a segment, the method further comprises:

classifying a segment to a target user.

12 . The computer-implemented method of claim 1 , wherein, before transcribing the voice included in a segment, the method further comprises:

extracting audio features included in the segment, the segment belonging to a target user; and

detecting emotion of the user based on the extracted audio features.

13 . The computer-implemented method of claim 1 , wherein performing natural language processing on the text further comprises:

filtering out irrelevant information from the text.

14 . The computer-implemented method of claim 1 , wherein performing natural language processing on the text comprises:

performing a sentiment analysis of the text.

15 . The computer-implemented method of claim 1 , wherein performing natural language processing on the text comprises:

performing an intent classification of a target user based on the text.

16 . The computer-implemented method of claim 1 , further comprises:

publishing insights obtained from the segments using a pub/sub process.

17 . The computer-implemented method of claim 1 , wherein the audio stream comprises a plurality of channels of audio stream.

18 . The computer-implemented method of claim 17 , wherein splitting the audio stream into segments using a producer-consumer algorithm further comprises:

creating a worker architecture comprising a plurality of audio processing channel workers, wherein each audio processing channel worker implements a producer-consumer algorithm-based process to split one channel of audio stream.

19 . The computer-implemented method of claim 18 , wherein the worker architecture further comprises a plurality of content filtering workers, each content filtering worker implementing a content filtering process to remove noise or irrelevant information from the segments or text transcribed from the segments.

20 . A system for processing an audio stream, comprising:

a processor; and

a memory, coupled to the processor, configured to store executable instructions that, when executed by the processor, cause the processor to perform operations including:

receiving an audio stream by a node;

splitting the audio stream into segments using a producer-consumer algorithm in a memory of the node, the audio stream being split into the segments based on silence detection;

transcribing voice included in a segment into text using a voice-to-text conversion engine; and

performing natural language processing on the text to identify situational insights from the segment.

Assignments (3)
CORRECTIVE ASSIGNMENT TO CORRECT THE CONVEYANCE TYPE OF MERGER PREVIOUSLY RECORDED ON REEL 66511 FRAME 683. ASSIGNOR(S) HEREBY CONFIRMS THE CONVEYANCE TYPE OF ASSIGNMENT. Recorded Feb 26, 2024
From: GENPACT LUXEMBOURG S.À R.L. II
To: GENPACT USA, INC.
Reel/Frame 067211/0020 →
MERGER Recorded Feb 7, 2024
From: GENPACT LUXEMBOURG S.À R.L. II
To: GENPACT USA, INC.
Reel/Frame 066511/0683 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 16, 2023
From: SAHA, RAHUL; SINGH, SIDDHARTH; DEO, JATINDRA SINGH; SRIVASTAVA, RAJAT; BISWAS, GOPE; MENON, SREEKANTH
To: GENPACT LUXEMBOURG S.À R.L. II
Reel/Frame 063655/0866 →