Results 41 to 50 of about 6,219 (212)
Mel-frequency cepstral coefficient-based bandwidth extension of narrowband speech [PDF]
Interspeech 2008, 2008 Abstract We present a novel MFCC-based scheme for the BandwidthExtension (BWE) of narrowband speech. BWE is based onthe assumption that narrowband speech (0.3–3.4 kHz) cor-relates closely with the highband signal (3.4–7 kHz), en-abling estimation of the highband frequency content given thenarrow band.
Amr H. Nour-Eldin, Peter Kabal
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Mel-frequency cepstral coefficients of voice source waveforms for classification of phonation types in speech [PDF]
, 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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MachinesTo fully exploit the rich state and fault information embedded in the acoustic signals of a hydraulic plunger pump, this paper proposes an intelligent diagnostic method based on sound signal analysis.
Liqiang Ma, Anqi Jiang, Wanlu Jiang
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SENTIMENT ANALYSIS ON SPEECH SIGNALS: LEVERAGING MFCC-LSTM TECHNIQUE FOR ENHANCED EMOTIONAL UNDERSTANDING [PDF]
Proceedings on Engineering SciencesThe analysis of emotions expressed in spoken language holds a pivotal role in human communication, artificial intelligence, and human-computer interaction. While emotion recognition in text has seen considerable advancements, recognizing emotional states
Suman Lata +2 more
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Spoken Digit Recognition using the k-Nearest-Neighbor method and Mel Frequency Cepstral Coefficients [PDF]
Informatică economicăThis study investigates the utilization of the k-nearest-neighbor algorithm within the framework of machine learning for speech recognition applications. The AudioMNIST dataset is used for performing the evaluations in which the model predicts the spoken
Sorin MURARU, Catalina Lucia COCIANU
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Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
Сучасний стан наукових досліджень та технологій в промисловості, 2023 The subject matter of the study is the analysis of the influence of pre-processing stages of the audio on the accuracy of speaker language regognition. The importance of audio pre-processing has grown significantly in recent years due to its key role in
Олеся Барковська +1 more
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Automatic Cough Detection from Audio Signals Using Deep Learning and Hybrid CNN–SVM Models [PDF]
EPJ Web of ConferencesCoughing is a natural physiological reflex that helps maintain respiratory health by clearing the airways of irritants, fluids, and pathogens. It also serves as a key clinical indicator for various respiratory conditions, including asthma, infections ...
Barkani Fatima +2 more
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Speech-Based Vehicle Movement Control Solution
Journal of Telecommunications and Information Technology, 2021 The article describes a speech-based robotic prototype designed to aid the movement of elderly or handicapped individuals. Mel frequency cepstral coefficients (MFCC) are used for the extraction of speech features and a deep belief network (DBN) is ...
Gurpreet Kaur +2 more
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Mel Frequency Cepstral Coefficient: A Review [PDF]
Proceedings of the 2nd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2020, 27-28 February 2020, Jamia Hamdard, New Delhi, India, 2021 Shalbbya Ali +3 more
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