# Music and Audio Processing

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/music-and-audio-processing/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the classification and analysis of audio signals, including music genre classification, environmental sound recognition, melody extraction, and acoustic scene classification. It explores techniques such as deep learning, convolutional neural networks, and feature extraction for music information retrieval. |
| Domain | Physical Sciences |
| Field | Computer Science |
| OpenAlex ID | t11309 |
| Works | 89 |

## Topic papers all

Showing 15 of 89.

- [SoundSense](https://scholariq.org/papers/soundsense/)
- [Transformer Transducer: A Streamable Speech Recognition Model with Transformer Encoders and RNN-T Loss](https://scholariq.org/papers/transformer-transducer-a-streamable-speech-recognition-model-with-transformer/)
- [A Comprehensive Review of Speech Emotion Recognition Systems](https://scholariq.org/papers/a-comprehensive-review-of-speech-emotion-recognition-systems/)
- [Very deep convolutional neural networks for raw waveforms](https://scholariq.org/papers/very-deep-convolutional-neural-networks-for-raw-waveforms/)
- [The influence of metricality and modality on synchronization with a beat](https://scholariq.org/papers/the-influence-of-metricality-and-modality-on-synchronization-with-a-beat/)
- [Feature Selection Based on L1-Norm Support Vector Machine and Effective Recognition System for Parkinson’s Disease Using Voice Recordings](https://scholariq.org/papers/feature-selection-based-on-l1-norm-support-vector-machine-and-effective/)
- [Long Short-Term Memory Recurrent Neural Network for Automatic Speech Recognition](https://scholariq.org/papers/long-short-term-memory-recurrent-neural-network-for-automatic-speech-recognition/)
- [The Random Forests statistical technique: An examination of its value for the study of reading](https://scholariq.org/papers/the-random-forests-statistical-technique-an-examination-of-its-value-for-the/)
- [Musical genre classification using support vector machines](https://scholariq.org/papers/musical-genre-classification-using-support-vector-machines/)
- [Early diagnosis of Parkinson’s disease from multiple voice recordings by simultaneous sample and feature selection](https://scholariq.org/papers/early-diagnosis-of-parkinson-s-disease-from-multiple-voice-recordings-by/)
- [Error back propagation for sequence training of Context-Dependent Deep NetworkS for conversational speech transcription](https://scholariq.org/papers/error-back-propagation-for-sequence-training-of-context-dependent-deep-networks/)
- [A comparison of Deep Learning methods for environmental sound detection](https://scholariq.org/papers/a-comparison-of-deep-learning-methods-for-environmental-sound-detection/)
- [How does music evoke emotions? Exploring the underlying mechanisms.](https://scholariq.org/papers/how-does-music-evoke-emotions-exploring-the-underlying-mechanisms/)
- [Faster and more accurate classification of time series by exploiting a novel dynamic time warping averaging algorithm](https://scholariq.org/papers/faster-and-more-accurate-classification-of-time-series-by-exploiting-a-novel/)
- [A computer-aided MFCC-based HMM system for automatic auscultation](https://scholariq.org/papers/a-computer-aided-mfcc-based-hmm-system-for-automatic-auscultation/)

## Topic primary papers

Showing 15 of 25.

- [SoundSense](https://scholariq.org/papers/soundsense/)
- [Very deep convolutional neural networks for raw waveforms](https://scholariq.org/papers/very-deep-convolutional-neural-networks-for-raw-waveforms/)
- [Musical genre classification using support vector machines](https://scholariq.org/papers/musical-genre-classification-using-support-vector-machines/)
- [A comparison of Deep Learning methods for environmental sound detection](https://scholariq.org/papers/a-comparison-of-deep-learning-methods-for-environmental-sound-detection/)
- [Speaker Gender Recognition Based on Deep Neural Networks and ResNet50](https://scholariq.org/papers/speaker-gender-recognition-based-on-deep-neural-networks-and-resnet50/)
- [Anomalous sound event detection: A survey of machine learning based methods and applications](https://scholariq.org/papers/anomalous-sound-event-detection-a-survey-of-machine-learning-based-methods-and/)
- [F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching](https://scholariq.org/papers/f5-tts-a-fairytaler-that-fakes-fluent-and-faithful-speech-with-flow-matching/)
- [Audio Classification Method Based on Machine Learning](https://scholariq.org/papers/audio-classification-method-based-on-machine-learning/)
- [Detecting Parkinsons' symptoms in uncontrolled home environments: A multiple instance learning approach](https://scholariq.org/papers/detecting-parkinsons-symptoms-in-uncontrolled-home-environments-a-multiple/)
- [Transformer-based ensemble method for multiple predominant instruments recognition in polyphonic music](https://scholariq.org/papers/transformer-based-ensemble-method-for-multiple-predominant-instruments/)
- [Bangla Short Speech Commands Recognition Using Convolutional Neural Networks](https://scholariq.org/papers/bangla-short-speech-commands-recognition-using-convolutional-neural-networks/)
- [Hybrid Multimodal Feature Extraction, Mining and Fusion for Sentiment Analysis](https://scholariq.org/papers/hybrid-multimodal-feature-extraction-mining-and-fusion-for-sentiment-analysis/)
- [Bird Call Classification Using DNN-Based Acoustic Modelling](https://scholariq.org/papers/bird-call-classification-using-dnn-based-acoustic-modelling/)
- [SVM based transcription system with short-term memory oriented to polyphonic piano music](https://scholariq.org/papers/svm-based-transcription-system-with-short-term-memory-oriented-to-polyphonic/)
- [Counting Mosquitoes in the Wild](https://scholariq.org/papers/counting-mosquitoes-in-the-wild/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.