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Wireless Standard Identification via Mel Frequency Cepstrum
IEEE Communications Letters, 2022Xuegang Wang +2 more
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Identification of Language using Mel-Frequency Cepstral Coefficients (MFCC)
Procedia Engineering, 2012 This paper focuses on the task of identifying a language from speech signal. In this paper, we have use Mel-frequency cepstral coefficient as features.
Shashidhar G Koolagudi
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2021 Innovations in Intelligent Systems and Applications Conference (ASYU), 2021
Digital multimedia security has taken a very important position with the developing technology. Detecting forgeries in audio signals is one of the most challenging application in the field of audio forensics. In this study, Mel Frequency and Delta Mel Frequency based methods are proposed to detect copypaste forgery in audio signals.
Fulya Akdeniz, Yaşar Becerikli
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Digital multimedia security has taken a very important position with the developing technology. Detecting forgeries in audio signals is one of the most challenging application in the field of audio forensics. In this study, Mel Frequency and Delta Mel Frequency based methods are proposed to detect copypaste forgery in audio signals.
Fulya Akdeniz, Yaşar Becerikli
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Compensated mel frequency cepstrum coefficients
1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings, 2002The high concentration of energy in the low frequency range observed for most speech spectra is considered a nuisance because it makes less relevant the energy of the signal at middle and high frequencies in many speech analysis algorithms. This problem is often partially solved by filtering the input signal with a single-zero high pass filter.
Rivarol Vergin +2 more
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Computing Mel-frequency cepstral coefficients on the power spectrum
2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002We present a method to derive Mel-frequency cepstral coefficients directly from the power spectrum of a speech signal. We show that omitting the filterbank in signal analysis does not affect the word error rate. The presented approach simplifies the speech recognizers front end by merging subsequent signal analysis steps into a single one.
Sirko Molau +3 more
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Audio Detection using Mel-frequency Cepstral Coefficients
2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), 2021The lack of benchmark findings for comparison with any suggested approach is one of the most fundamental challenges in sound event detection research. Distinct research explore different sets of events and datasets, making it difficult to distinguish between new and existing methods.
Uppu Jithendra +2 more
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Combined audio and video watermarking using mel-frequency cepstra
IEEE International Conference on Multimedia and Expo, 2001. ICME 2001., 2001Digital watermarking is a promising technique to help protect the data security and intellectual property right. In this paper a combined audio and video watermarking technique is proposed. Content-dependent information is extracted from the audio signal. The extraction uses a well-known feature set for audio, the melfrequency cepstra.
Qiang Cheng 0001 +2 more
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Cepstral analysis synthesis on the mel frequency scale
ICASSP '83. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005This paper presents a new technique of cepstral analysis synthesis on the mel frequency scale, the log spectrum on the mel frequency scale (the mel log spectrum) is considered to be an effective representation of the spectral envelope of speech. This analysis synthesis system uses the mel log spectrum approximation (MLSA) filter which was devised for ...
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Perturbation analysis of mel-frequency cepstrum coefficients
2010 International Conference on Audio, Language and Image Processing, 2010Mel-frequency cepstrum coefficient (MFCC) is a widely used feature vector in speech signal precessing. Its feature extraction procedure can be seen as a mapping function which transfers the input speech signals to output MFCC feature vectors. However, this function is too complex to analyze and even a simple approximation is not easy to obtain.
Wei-Qiang Zhang +3 more
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Chip design of mel frequency cepstral coefficients for speech recognition
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002The mel frequency cepstral coefficients (MFCC) is one of the mast important features, which is required among various kinds of speech applications. The chip for speech features extraction based on the MFCC algorithm is first proposed. The chip is designed with area efficient consideration and can achieve the following: (1) the reduction of table size ...
Jia-Ching Wang +2 more
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