# Evaluating the Performance of Long Short-Term Memory (LSTM) Model Variants Using Traditional Music Audio Dataset
> Kambau R.A.

URL kanonis: https://discover.unhas.ac.id/publications/evaluating-the-performance-of-long-short-term-memory-lstm-model-variants-using-t
Jurnal / Konferensi: Studies in Computational Intelligence
Tahun terbit: 2026
DOI: https://doi.org/10.1007/978-3-032-01133-6_25
ISSN: 1860949X
Kuartil SJR: Q4
Citations: 0

## Authors
- Kambau R.A.

## Abstract
Sourced directly from Elsevier Scopus. No OpenAlex abstract available.

## Keywords
- Computer science
- Residual
- Speech recognition
- Mel-frequency cepstrum
- Artificial intelligence
- Cepstrum
- Sound recording and reproduction
- Long short term memory
- Audio signal
- Audio analyzer
- Audio signal processing
- Pattern recognition (psychology)
- Digital audio
- Machine learning
- Musical
- Music information retrieval
- Sound quality
- Deep learning
- Musical tone
- Training set
- Natural language processing

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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