Raw-Waveform Based Bark Scale Initialized SincNet Model in Child Speaker Identification DOI
Kodali Radha,

Jami Gowtham Kumar,

D. Sanjay

et al.

Published: Aug. 2, 2024

Language: Английский

Automatic dysarthria detection and severity level assessment using CWT-layered CNN model DOI Creative Commons

Shaik Sajiha,

Kodali Radha,

Dhulipalla Venkata Rao

et al.

EURASIP Journal on Audio Speech and Music Processing, Journal Year: 2024, Volume and Issue: 2024(1)

Published: June 25, 2024

Abstract Dysarthria is a speech disorder that affects the ability to communicate due articulation difficulties. This research proposes novel method for automatic dysarthria detection (ADD) and severity level assessment (ADSLA) by using variable continuous wavelet transform (CWT) layered convolutional neural network (CNN) model. To determine their efficiency, proposed model assessed two distinct corpora, TORGO UA-Speech, comprising both patients healthy subject signals. The study explores effectiveness of CWT-layered CNN models employ different wavelets such as Amor, Morse, Bump. aims analyze models’ performance without need feature extraction, which could provide deeper insights into in processing complex data. Also, raw waveform modeling preserves original signal’s integrity nuance, making it ideal applications like recognition, signal processing, image processing. Extensive analysis experimentation have revealed Amor surpasses Morse Bump accurately representing characteristics. outperforms others terms reconstruction fidelity, noise suppression capabilities, extraction accuracy. emphasizes importance selecting appropriate signal-processing tasks. reliable precise choice applications. UA-Speech dataset crucial more accurate classification. Advanced deep learning techniques can simplify early intervention measures expedite diagnosis process.

Language: Английский

Citations

4
Temporal feature-based approaches for enhancing phoneme boundary detection and masking in speech DOI
Shaik Mulla Shabber, Mohan Bansal

International Journal of Speech Technology, Journal Year: 2024, Volume and Issue: 27(2), P. 425 - 436

Published: June 1, 2024

Language: Английский

Citations

1
Automated ASD detection in children from raw speech using customized STFT-CNN model DOI

Kurma Venkata Keerthana Sai,

Rompicharla Thanmayee Krishna,

Kodali Radha

et al.

International Journal of Speech Technology, Journal Year: 2024, Volume and Issue: 27(3), P. 701 - 716

Published: July 26, 2024

Language: Английский

Citations

0
Raw-Waveform Based Bark Scale Initialized SincNet Model in Child Speaker Identification DOI
Kodali Radha,

Jami Gowtham Kumar,

D. Sanjay

et al.

Published: Aug. 2, 2024

Language: Английский

Citations

0