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Unlocking Potential in Pre-Trained Music Language Models for Versatile Multi-Track Music Arrangement
Large language models have shown significant capabilities across various domains, including symbolic music generation. However, leveraging these pre-trained models for controllable music arrangement tasks, each requiring different forms of musical in
Externí odkaz:
http://arxiv.org/abs/2408.15176
Despite previous efforts in melody-to-lyric generation research, there is still a significant compatibility gap between generated lyrics and melodies, negatively impacting the singability of the outputs. This paper bridges the singability gap with a
Externí odkaz:
http://arxiv.org/abs/2307.02146
The development of general-domain neural machine translation (NMT) methods has advanced significantly in recent years, but the lack of naturalness and musical constraints in the outputs makes them unable to produce singable lyric translations. This p
Externí odkaz:
http://arxiv.org/abs/2305.16816
Singing voice transcription converts recorded singing audio to musical notation. Sound contamination (such as accompaniment) and lack of annotated data make singing voice transcription an extremely difficult task. We take two approaches to tackle the
Externí odkaz:
http://arxiv.org/abs/2304.12082
Automatic speech recognition (ASR) has progressed significantly in recent years due to the emergence of large-scale datasets and the self-supervised learning (SSL) paradigm. However, as its counterpart problem in the singing domain, the development o
Externí odkaz:
http://arxiv.org/abs/2207.09747
Automatic lyric transcription (ALT) is a nascent field of study attracting increasing interest from both the speech and music information retrieval communities, given its significant application potential. However, ALT with audio data alone is a noto
Externí odkaz:
http://arxiv.org/abs/2207.06127
Most recent research about automatic music transcription (AMT) uses convolutional neural networks and recurrent neural networks to model the mapping from music signals to symbolic notation. Based on a high-resolution piano transcription system, we ex
Externí odkaz:
http://arxiv.org/abs/2204.03898
Machine learning algorithms have made remarkable achievements in the field of artificial intelligence. However, most machine learning algorithms are sensitive to the hyper-parameters. Manually optimizing the hyper-parameters is a common method of hyp
Externí odkaz:
http://arxiv.org/abs/2003.01751
Akademický článek
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Publikováno v:
Proceedings of the 30th ACM International Conference on Multimedia.
Automatic lyric transcription (ALT) is a nascent field of study attracting increasing interest from both the speech and music information retrieval communities, given its significant application potential. However, ALT with audio data alone is a noto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba33194a71dbe4e4b647157474bcd49f
https://doi.org/10.1145/3503161.3548411
https://doi.org/10.1145/3503161.3548411
