View source for Samsung electronics co., ltd. (20240119943). APPARATUS FOR IMPLEMENTING SPEAKER DIARIZATION MODEL, METHOD OF SPEAKER DIARIZATION, AND PORTABLE TERMINAL INCLUDING THE APPARATUS simplified abstract

=APPARATUS FOR IMPLEMENTING SPEAKER DIARIZATION MODEL, METHOD OF SPEAKER DIARIZATION, AND PORTABLE TERMINAL INCLUDING THE APPARATUS=


==Organization Name==

[[:Category:samsung electronics co., ltd.|samsung electronics co., ltd.]]


[[Category:samsung electronics co., ltd.]]

==Inventor(s)==

[[:Category:Wan Ju Kang of Daejeon (KR)|Wan Ju Kang of Daejeon (KR)]][[Category:Wan Ju Kang of Daejeon (KR)]]

[[:Category:Sungju Lee of Daejeon (KR)|Sungju Lee of Daejeon (KR)]][[Category:Sungju Lee of Daejeon (KR)]]

[[:Category:Ryuhaerang Choi of Daejeon (KR)|Ryuhaerang Choi of Daejeon (KR)]][[Category:Ryuhaerang Choi of Daejeon (KR)]]

==APPARATUS FOR IMPLEMENTING SPEAKER DIARIZATION MODEL, METHOD OF SPEAKER DIARIZATION, AND PORTABLE TERMINAL INCLUDING THE APPARATUS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240119943 titled 'APPARATUS FOR IMPLEMENTING SPEAKER DIARIZATION MODEL, METHOD OF SPEAKER DIARIZATION, AND PORTABLE TERMINAL INCLUDING THE APPARATUS

==Simplified Explanation==

The speaker diarization model implementing apparatus described in the abstract is a system that can separate multiple speakers from each other using voice signals and motion sensing signals. Here is a simplified explanation of the patent application:

* Voice signal analysis module generates mel-spectrogram data from voice signals of multiple speakers.
* Motion data analysis module generates ultra-wideband (uwb) signal matrix data from motion sensing signals of the speakers.
* Multimodal learning module extracts characteristic values from the mel-spectrogram data and uwb signal matrix data.
* Speaker diarization module separates the speakers using the characteristic values.

### Potential Applications
This technology can be used in conference call systems, surveillance systems, and voice-controlled devices to accurately identify and separate speakers.

### Problems Solved
This technology solves the problem of accurately identifying and separating multiple speakers in various audio and motion sensing applications.

### Benefits
The benefits of this technology include improved accuracy in speaker identification, enhanced user experience in voice-controlled devices, and better organization of audio data in surveillance systems.

### Potential Commercial Applications
A potential commercial application of this technology could be in the development of advanced conference call systems for businesses.

### Possible Prior Art
One possible prior art for speaker diarization technology is the use of machine learning algorithms to separate speakers in audio recordings.

#### Unanswered Questions

#### How does this technology handle background noise in speaker diarization?
The abstract does not mention how the apparatus deals with background noise that may affect speaker separation accuracy.

#### Can this technology be integrated with existing voice recognition systems?
It is not clear from the abstract whether this speaker diarization model can be easily integrated with current voice recognition technologies.


==Original Abstract Submitted==

a speaker diarization model implementing apparatus includes a voice signal analysis module configured to generate mel-spectrogram data from voice signals of a plurality of speakers detected by a voice recognition device, a motion data analysis module configured to generate ultra-wideband (uwb) signal matrix data from motion sensing signals of the plurality of speakers detected by a motion recognition device, a multimodal learning module configured to extract characteristic values based on the mel-spectrogram data and the uwb signal matrix data, and a speaker diarization module configured to separate the plurality of speakers from each other using the characteristic values.



[[Category:G10L17/10]]
[[Category:G10L17/18]]