Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
98%
921
2 minutes
20
Speech recognition in noisy environments has long posed a challenge. Air conduction microphone (ACM), the devices typically used, are susceptible to environmental noise. In this work, a customized bone conduction microphone (BCM) system based on a piezoelectric micromachined ultrasonic transducer is developed to capture speech through real-time bone conduction (BC), while a commercial ACM is integrated for simultaneous capture of speech through air conduction (AC). The system enables simpler and more robust BC speech capture. The BC speech capture achieves a signal-to-noise amplitude ratio over five times greater than that of AC speech capture in an environment with a noise level of 68 dB. Instead of using only AC-captured speech, both BC- and AC-captured speech are input into a speech enhancement module. The noise-insensitive BC-captured speech serves as a speech reference to adapt the SE backbone of AC-captured speech. The two types of speech are fused, and noise suppression is applied to generate enhanced speech. Compared with the original noisy speech, the enhanced speech achieves a character error rate reduction of over 20%, approaching the speech recognition accuracy of clean speech. The results indicate that this speech enhancement method based on the fusion of BC- and AC-captured speech efficiently integrates the features of both types of speech, thereby improving speech recognition accuracy in noisy environments. This work presents an innovative system designed to efficiently capture BC speech and enhance speech recognition in noisy environments.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12195400 | PMC |
http://dx.doi.org/10.3390/mi16060613 | DOI Listing |