Phonetic-acoustic database of trigrams for Russian dialects speech recognition

Butenko, Iuliia; Slavnov, Nikolay; Stroganov, Yuriy; Kvasnikov, Alexander

doi:10.1063/5.0151706

The International Conference on Battery for Renewable Energy and Electric Vehicles (Icb-Rev) 2022

2023

DOI: 10.1063/5.0151706

|View full text |Cite

Phonetic-acoustic database of trigrams for Russian dialects speech recognition

Iuliia Butenko,

Nikolay Slavnov,

Yuriy Stroganov

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Two-stage algorithm of spectral analysis for the automatic speech recognition systems

Savchenko,

Savchenko

2024

Meas Tech

View full text Add to dashboard Cite

Two-stage algorithm of spectral analysis for the automatic speech recognition systems

Savchenko,

Savchenko

2024

Meas Tech

View full text Add to dashboard Cite

Two-stage algorithm of spectral analysis for automatic speech recognition systems

Savchenko,

Savchenko

2024

jour

View full text Add to dashboard Cite

Within the framework of a dynamically developing direction of research in the field of acoustic measurements, the task of spectral analysis of speech signals in automatic speech recognition systems is considered. The low efficiency of the systems in unfavorable speech production conditions (noise, insufficient intelligibility of speech sounds) compared to human perception of oral speech is noted. To improve the efficiency of automatic speech recognition systems, a two-stage algorithm for spectral analysis of speech signals is proposed. The first stage of speech signal processing consists of its parametric spectral analysis using an autoregressive model of the vocal tract of a conditional speaker. The second stage of processing is the transformation (modification) of the obtained spectral estimate according to the principle of frequency-selective amplification of the amplitude of the main formants of the intra-periodic power spectrum. The software implementation of the proposed algorithm based on the high-speed computational procedure of the fast Fourier transform is described. Using the author’s software, a full-scale experiment was carried out: an additive mixture of vowel sounds of the control speaker’s speech with white Gaussian noise was studied. Based on the results of the experiment, it was concluded that the amplitude of the main speech signal formants were amplified by 10–20 dB and, accordingly, a significant improvement in the speech sounds intelligibility. The scope of possible application of the developed algorithm covers automatic speech recognition systems based on speech signal processing in the frequency domain, including the use of artificial neural networks.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Phonetic-acoustic database of trigrams for Russian dialects speech recognition

Cited by 2 publications

References 16 publications

Two-stage algorithm of spectral analysis for the automatic speech recognition systems

Two-stage algorithm of spectral analysis for the automatic speech recognition systems

Two-stage algorithm of spectral analysis for automatic speech recognition systems

Contact Info

Product

Resources

About