Results 21 to 30 of about 1,013,210 (107)
LVNS-RAVE: Diversified audio generation with RAVE and Latent Vector Novelty Search
Evolutionary Algorithms and Generative Deep Learning have been two of the most powerful tools for sound generation tasks. However, they have limitations: Evolutionary Algorithms require complicated designs, posing challenges in control and achieving ...
Christodoulou, Anna-Maria +3 more
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Active Bird2Vec: Towards End-to-End Bird Sound Monitoring with Transformers
, 2023 We propose a shift towards end-to-end learning in bird sound monitoring by combining self-supervised (SSL) and deep active learning (DAL). Leveraging transformer models, we aim to bypass traditional spectrogram conversions, enabling direct raw audio ...
Rauch, Lukas +5 more
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, 2023 While recent generative models can produce engaging music, their utility is limited. The variation in the music is often left to chance, resulting in compositions that lack structure.
Atassi, Lilac
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Experimental study on deep learning for spectrum reconstruction of damaged audio signals [PDF]
openThis thesis presents an experimental study on the application of deep learning techniques for the spectrum reconstruction of damaged audio signals.
VERZOTTO, LAVINIA
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, 2023 In this work, we propose a method for the controllable synthesis of real-time contact sounds using neural resonators. Previous works have used physically inspired statistical methods and physical modelling for object materials and excitation signals. Our
Diaz, Rodrigo +2 more
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Regularized Contrastive Pre-training for Few-shot Bioacoustic Sound Detection
, 2023 Bioacoustic sound event detection allows for better understanding of animal behavior and for better monitoring biodiversity using audio. Deep learning systems can help achieve this goal, however it is difficult to acquire sufficient annotated data to ...
Farrugia, Nicolas +2 more
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A Mapping Strategy for Interacting with Latent Audio Synthesis Using Artistic Materials [PDF]
This paper presents a mapping strategy for interacting with the latent spaces of generative AI models. Our approach involves using unsupervised feature learning to encode a human control space and mapping it to an audio synthesis model's latent space. To
Bryan-Kinns, N +3 more
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A Survey of Music Generation in the Context of Interaction
In recent years, machine learning, and in particular generative adversarial neural networks (GANs) and attention-based neural networks (transformers), have been successfully used to compose and generate music, both melodies and polyphonic pieces. Current
Agchar, Ismael +6 more
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ParaCLAP -- Towards a general language-audio model for computational paralinguistic tasks
Contrastive language-audio pretraining (CLAP) has recently emerged as a method for making audio analysis more generalisable. Specifically, CLAP-style models are able to `answer' a diverse set of language queries, extending the capabilities of audio ...
Jing, Xin +2 more
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A Practical Guide to Spectrogram Analysis for Audio Signal Processing
The paper summarizes spectrogram and gives practical application of spectrogram in signal processing. For analysis, finger-snapping is recorded with a sampling rate of 441000 Hz and 96000 Hz.
Khodzhaev, Zulfidin
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