Results 71 to 80 of about 3,617,625 (210)
The Impact of Speaking Style on Speaker Classification Using Mel-Frequency Cepstral Coefficients [PDF]
زبان پژوهیThis research investigates the impact of different speaking styles (read and spontaneous) on speaker identification accuracy. Mel-Frequency Cepstral Coefficients (MFCCs) were employed as input features, and the Random Forest algorithm was used for ...
Homa Asadi
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Soft Active Electromyography Interface for Machine Learning‐Enabled Silent Speech Recognition
Advanced Intelligent Systems, Volume 8, Issue 9, September 2026.A soft, hand‐worn electromyography interface enables intent‐driven silent speech recognition without continuous facial attachment. The device integrates liquid‐metal interconnects, a transparent flexible circuit, and elastomer encapsulation with a fingertip electrode that contacts perioral muscles only on demand.
Yuta Kurotaki +8 more
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IEEE AccessWavelet-based front-ends have been extensively utilized in speech processing systems, particularly for recognizing speech and speakers, and have significantly improved their performance.
Ibrahim Missaoui, Zied Lachiri
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<p>For a project description please look at <a href="https://github.com/jasminsternkopf/mel_cepstral_distance">GitHub</a>/<a href="https://pypi.org/project/mel-cepstral-distance">PyPI</a>.</p ...
Taubert, Stefan, Sternkopf, Jasmin
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, 2014 We propose a method for minimum mean-square error (MMSE) estimation of mel-frequency cepstral features for noise robust automatic speech recognition (ASR).
Tan, Zheng-Hua; id_orcid +3 more
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On the Optimal Selection of Mel‐Frequency Cepstral Coefficients for Voice Deepfake Detection
Expert SystemsABSTRACT The continuous evolution of techniques for generating manipulated audio, known as voice deepfakes, and the widespread availability of tools that produce convincing forgeries have created an urgent need for reliable detection methods.
Sergio A. Falcón-López +3 more
openaire +2 more sources
Feature Extracting in the Presence of Environmental Noise, using Subband Adaptive Filtering [PDF]
, 2009 In this work, a new feature extracting method in noisy environments is proposed. The approach is based on subband decomposition of speech signals followed by adaptive filtering in the noisiest subbbands of speech.
Samad, Salina Abdul
core
Developmental Science, Volume 29, Issue 4, July 2026.ABSTRACT Human newborns are able to discriminate between certain languages but not others. This ability has long been attributed to sensitivity to rhythm—the temporal regularities in speech of different languages. Here, we demonstrate through a series of computational simulations that this discrimination behavior can be achieved using no temporal ...
Ruolan Leslie Famularo +3 more
wiley +1 more source
, 2019 Voice source characteristics in different phonation types vary due to the tension of laryngeal muscles along with the respiratory effort. This study investigates the use of mel-frequency cepstral coefficients (MFCCs) derived from voice source waveforms ...
Kadiri, Sudarsana Reddy +3 more
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Automatic Speaker Recognition Based on Mel-Frequency Cepstral Coefficients and Gaussian Mixture Models [PDF]
Mehran University Research Journal of Engineering and Technology, 2013 This paper investigates the task of SR (Speaker Recognition) for the state-of-the-art techniques. The paper initially presents the technical description of automatic SR, followed by the comparative analysis of a number of methods available for feature ...
Sheeraz Memon +2 more
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