Results 11 to 20 of about 7,229,432 (222)
A Mel Spectrogram Enhancement Paradigm Based on CWT in Speech Synthesis [PDF]
2024 International Conference on Asian Language Processing (IALP)Acoustic features play an important role in improving the quality of the synthesised speech. Currently, the Mel spectrogram is a widely employed acoustic feature in most acoustic models.
Guoqiang Hu, Huaning Tan
exaly +5 more sources
Mel spectrogram-based audio forgery detection using CNN
Signal, Image and Video Processing, 2022 In this time of technology, digital speech can be created and falsified by a very diverse of hardware and software technologies. Audio copy-move forgery is an audio forgery technique that goals to create forged audio by hiding undesirable words or ...
Arda Ustubioglu +2 more
semanticscholar +4 more sources
Mel-Weighted Single Frequency Filtering Spectrogram for Dialect Identification [PDF]
IEEE Access, 2020 In this study, we propose Mel-weighted single frequency filtering (SFF) spectrograms for dialect identification. The spectrum derived using SFF has high spectral resolution for harmonics and resonances while simultaneously maintaining good time ...
Rashmi Kethireddy +2 more
exaly +4 more sources
Cough Recognition Based on Mel-Spectrogram and Convolutional Neural Network [PDF]
Frontiers in Robotics and AI, 2021 In daily life, there are a variety of complex sound sources. It is important to effectively detect certain sounds in some situations. With the outbreak of COVID-19, it is necessary to distinguish the sound of coughing, to estimate suspected patients in the population.
Quan Zhou, Jianhua Shan, Wenlong Ding
exaly +6 more sources
Voice pathology identification using mel spectrogram features and deep learning [PDF]
Signal, Image and Video ProcessingVoice pathology is very important in the identification of vocal disorders. Traditional methods of diagnosing voice disorders using voice pathology are expensive, time-consuming, and subjective.
R. Bashir +6 more
semanticscholar +4 more sources
Applied Sciences, 2022 The performance of speaker recognition systems is very well on the datasets without noise and mismatch. However, the performance gets degraded with the environmental noises, channel variation, physical and behavioral changes in speaker.
Wondimu Lambamo +2 more
doaj +2 more sources
A sinusoidal signal reconstruction method for the inversion of the mel-spectrogram [PDF]
2021 IEEE International Symposium on Multimedia (ISM), 2021 The synthesis of sound via deep learning methods has recently received much attention. Some problems for deep learning approaches to sound synthesis relate to the amount of data needed to specify an audio signal and the necessity of preserving both the long and short time coherence of the synthesised signal.
Natsiou, Anastasia, O'Leary, Sean
openaire +7 more sources
Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions [PDF]
2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017 This paper describes Tacotron 2, a neural network architecture for speech synthesis directly from text. The system is composed of a recurrent sequence-to-sequence feature prediction network that maps character embeddings to mel-scale spectrograms ...
Jonathan Shen +12 more
semanticscholar +4 more sources
Applied Sciences, 2023 Predicting the remaining time before the next earthquake based on seismic signals generated in a laboratory setting is a challenging research task that is of significant importance for earthquake hazard assessment.
Bo Zhang +3 more
doaj +2 more sources
Text-only domain adaptation for end-to-end ASR using integrated text-to-mel-spectrogram generator [PDF]
Interspeech, 2023 We propose an end-to-end Automatic Speech Recognition (ASR) system that can be trained on transcribed speech data, text-only data, or a mixture of both. The proposed model uses an integrated auxiliary block for text-based training.
Vladimir Bataev +4 more
semanticscholar +3 more sources