Adaptive regularized spectral reduction for stabilizing ill-conditioned bone-conducted speech signals
Bone-conducted (BC) speech signals are inherently challenging to analyze due to their wide frequency range, which leads to ill-conditioning in numerical analysis and linear prediction (LP) techniques. This ill-conditioning is primarily caused by the expansion of eigenvalues, which complicates the st...
Saved in:
| Main Authors: | Kanwar Muhammad Afaq, Ammar Amjad, Li-Chia Tai, Hsien-Tsung Chang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2025-05-01
|
| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-2906.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
INTELLIGIBILITY OF THE KAZAKH SPEECH WHEN IT'S PROTECTED WITH COMBINED MASKING SIGNALS
by: Y. N. Seitkulov, et al.
Published: (2020-03-01) -
Speech Emotion Recognition Based on Voice Fundamental Frequency
by: Teodora DIMITROVA-GREKOW, et al.
Published: (2019-04-01) -
PHYSIOLOGICAL ASPECTS FOR SONOGRAMS BUILDING AND SPECTRUM RESTORE DISTORTED SPEECH VOCALIZATIONS
by: Mikhail V. Alyushin, et al.
Published: (2025-05-01) -
Advances in Automated Voice Pathology Detection: A Comprehensive Review of Speech Signal Analysis Techniques
by: Anitha Sankaran, et al.
Published: (2024-01-01) -
“Eh? Aye!”: Categorisation bias for natural human vs AI-augmented voices is influenced by dialect
by: Neil W. Kirk
Published: (2025-05-01)