Results 61 to 70 of about 3,463 (178)
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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Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Advanced Materials, Volume 38, Issue 40, 17 July 2026.Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source
ARO-The Scientific Journal of Koya University, 2020 A new technique of hiding a speech signal clip inside a digital color image is proposed in this paper to improve steganography security and loading capacity.
Yazen A. Khaleel
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The Capacity Of Mel Frequency Cepstral Coefficients For Speech Recognition
, 2017 Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output.
Al-Anzi, Fawaz S., Dia AbuZeina
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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
Доклады Белорусского государственного университета информатики и радиоэлектроникиThe problem of recognizing emotions in a speech signal using mel-frequency cepstral coefficients using a classifier based on the support vector machine has been studied. The RAVDESS data set was used in the experiments.
D. V. Krasnoproshin, M. I. Vashkevich
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Inter‐Model Feature Fusion for Robust Low‐Resource Speech Recognition
Applied AI Letters, Volume 7, Issue 2, June 2026.Our Self‐Supervised Feature Fusion (SSF‐FT) method enhances low‐resource speech recognition by adaptively combining features from self‐supervised models trained with Contrastive, Predictive, and Reconstruction objectives. This attention‐weighted ensemble delivers robust performance, particularly in acoustically challenging conditions, extending current
Ussen Kimanuka +2 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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Application of Music Data Visualization Technology in Music Appreciation Teaching
Engineering Reports, Volume 8, Issue 6, June 2026.The simulation environment is used to simulate real‐world music appreciation scenarios. DL is employed to preprocess music data, extract features, and identify rhythm information, which is then associated with visual design parameters to construct a parametric model.
Xiaowei Chen
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Construction and Application of GAN Enhanced Virtual Interpretation Model for Sports Communication
Engineering Reports, Volume 8, Issue 6, June 2026.This model is an end‐to‐end framework. Firstly, the style‐based generation network Style‐based GAN2 (StyleGAN2) is used to generate a highly realistic and adjustable static narrator portrait. Then, Bi‐directional Long Short‐Term Memory (Bi‐LSTM) is used to encode the Mel‐frequency Cepstral Coefficients (MFCCs), phonemes, and prosodic features of the ...
Li Zhang +3 more
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