Results 51 to 60 of about 7,229,432 (222)
cMelGAN: An Efficient Conditional Generative Model Based on Mel Spectrograms
CoRR, 2022 Analysing music in the field of machine learning is a very difficult problem with numerous constraints to consider. The nature of audio data, with its very high dimensionality and widely varying scales of structure, is one of the primary reasons why it is so difficult to model.
Tracy Qian +2 more
openaire +2 more sources
An investigation of the reconstruction capacity of stacked convolutional autoencoders for log-mel-spectrograms [PDF]
2022 16th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2022 In audio processing applications, the generation of expressive sounds based on high-level representations demonstrates a high demand. These representations can be used to manipulate the timbre and influence the synthesis of creative instrumental notes. Modern algorithms, such as neural networks, have inspired the development of expressive synthesizers ...
Anastasia Natsiou +2 more
openaire +2 more sources
Environment Sound Classification Based on Visual Multi-Feature Fusion and GRU-AWS
IEEE Access, 2020 There are two major questions regarding Environmental Sound Classification (ESC). What is the best audio recognition framework, and what is the most robust audio feature?
Ning Peng +6 more
doaj +1 more source
Empirical Mode Decomposition-Based Feature Extraction for Environmental Sound Classification
Sensors, 2022 In environment sound classification, log Mel band energies (MBEs) are considered as the most successful and commonly used features for classification. The underlying algorithm, fast Fourier transform (FFT), is valid under certain restrictions.
Ammar Ahmed +3 more
doaj +1 more source
, 2022 The log-Mel spectrogram of the waveform according to the selected dysarthria types (no evidence of dysarthria, hypokinetic dysarthria, and ataxic dysarthria) for each autumn and number protocol.
Jin Whan Cho (11592603) +13 more
core +1 more source
Autovocoder: fast waveform generation from a learned speech representation using differentiable digital signal processing [PDF]
, 2023 Most state-of-the-art Text-to-Speech systems use the mel-spectrogram as an intermediate representation, to decompose the task into acoustic modelling and waveform generation.
Webber, Jacob J., +9 more
core +1 more source
Theoretical and Applied Mechanics Letters, 2023 Wind turbine blades are prone to failure due to high tip speed, rain, dust and so on. A surface condition detecting approach based on wind turbine blade aerodynamic noise is proposed.
Weijun Zhu +5 more
doaj +1 more source
Detection of Abnormal Symptoms Using Acoustic-Spectrogram-Based Deep Learning
Applied SciencesAcoustic data inherently contain a variety of information, including indicators of abnormal symptoms. In this study, we propose a method for detecting abnormal symptoms by converting acoustic data into spectrogram representations and applying a deep ...
Seong-Yoon Kim +3 more
doaj +1 more source
A voiceprint pattern recognition method of smoothing reactor based on CNN
Zhejiang dianli, 2023 In order to accurately identify the operating condition of the smoothing reactor， a deep learning method based on CNN （convolutional neural network） is introduced.
HU Jingen +3 more
doaj +1 more source
Non-Intrusive Air Traffic Control Speech Quality Assessment with ResNet-BiLSTM
Applied Sciences, 2023 In the current field of air traffic control speech, there is a lack of effective objective speech quality evaluation methods. This paper proposes a new network framework based on ResNet–BiLSTM to address this issue.
Yuezhou Wu, Guimin Li, Qiang Fu
doaj +1 more source