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Found 10 papers, 4 papers with code
Audio Tagging With Connectionist Temporal Classification Model Using Sequential Labelled Data
To use the order information of sound events, we propose sequential labelled data (SLD), where both the presence or absence and the order information of sound events are known.
Synthesising Expressiveness in Peking Opera via Duration Informed Attention Network
This paper presents a method that generates expressive singing voice of Peking opera.
Peking Opera Synthesis via Duration Informed Attention Network
In this work, we propose to deal with this issue and synthesize expressive Peking Opera singing from the music score based on the Duration Informed Attention Network (DurIAN) framework.
A novel dataset for the identification of computer generated melodies in the CSMT challenge
The aim of the dataset is to examine whether it is possible to distinguish computer generated melodies by learning the feature of generated melodies.
An Encoder-Decoder Based Audio Captioning System With Transfer and Reinforcement Learning
Automated audio captioning aims to use natural language to describe the content of audio data.
Keyword Spotting System and Evaluation of Pruning and Quantization Methods on Low-power Edge Microcontrollers
The result also verified that the performance improvement for quantization and SIMD instruction.
An investigation on selecting audio pre-trained models for audio captioning
In this paper, a series of pre-trained models are investigated for the correlation between extracted audio features and the performance of audio captioning.
Extract fundamental frequency based on CNN combined with PYIN
Analysing the different performance of these two methods, PYIN is applied to supplement the F0 extracted from the trained CNN model to combine the advantages of these two algorithms.
Visually-Aware Audio Captioning With Adaptive Audio-Visual Attention
Audio captioning aims to generate text descriptions of audio clips.
An Comparative Analysis of Different Pitch and Metrical Grid Encoding Methods in the Task of Sequential Music Generation
Results display a general phenomenon of over-fitting from two aspects, the pitch embedding space and the test loss of the single-token grid encoding.
