Audio signal processing device and method for synchronizing speech and text by using machine learning model
US-2024321265-A1 · Sep 26, 2024 · US
US2015073794A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2015073794-A1 |
| Application number | US-201414307426-A |
| Country | US |
| Kind code | A1 |
| Filing date | Jun 17, 2014 |
| Priority date | Apr 1, 2011 |
| Publication date | Mar 12, 2015 |
| Grant date | — |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
In syllable or vowel or phone boundary detection during speech, an auditory spectrum may be determined for an input window of sound and one or more multi-scale features may be extracted from the auditory spectrum. Each multi-scale feature can be extracted using a separate two-dimensional spectro-temporal receptive filter. One or more feature maps corresponding to the one or more multi-scale features can be generated and an auditory gist vector can be extracted from each of the one or more feature maps. A cumulative gist vector may be obtained through augmentation of each auditory gist vector extracted from the one or more feature maps. One or more syllable or vowel or phone boundaries in the input window of sound can be detected by mapping the cumulative gist vector to one or more syllable or vowel or phone boundary characteristics using a machine learning algorithm.
Opening claim text (preview).
What is claimed is: 1 . A method, comprising: extracting one or more multi-scale features from an auditory spectrum for an input window of sound, wherein each multi-scale feature is extracted using a separate two-dimensional spectro-temporal receptive filter; generating one or more feature maps corresponding to the one or more multi-scale features; extracting an auditory gist vector from each of the one or more feature maps; obtaining a cumulative gist vector through augme…
Related publications grouped by family.
Free tools are coming soon. Tell us what you want to track and we'll notify you.
Answers are generated from the same data shown on this page.