Gerçek zamanlı akor tanımlama uygulaması: Ses işleme ve makine öğreniminin kusursuz entegrasyonuyla ömür boyu müzik eğitimini mümkün kılıyor

Öz

Ömür boyu müzik eğitimi, özellikle yetişkin öğrenciler ve yaşlılar olmak üzere herkes için kritik bir ihtiyaçtır. Müzik eğitimindeki zorluklardan biri akorları doğru bir şekilde belirlemektir. Bu, Yapay Zeka (AI) teknolojilerini kullanarak bir akor tanımlama uygulaması geliştirmek için yapılan bir ön çalışmadır. Ses işleme algoritmalarının ve derin öğrenme modellerinin yetişkin öğrencilerin ve yaşlı vatandaşların çeşitli ihtiyaçlarını karşılayan gerçek zamanlı, doğru ve kullanıcı dostu akor tanıma sağlamak için nasıl kullanılabileceği konusundaki temel araştırma sorusunu yanıtlamayı amaçlıyorum. Genel hedefimiz yalnızca akor tanımlamaya yardımcı olmakla kalmayıp aynı zamanda müzik ve öğrenmeye yönelik ömür boyu bir sevgiyi de teşvik eden bir uygulama yaratmaktır. Metodolojim yetişkin ve yaşlı eğitim girişimlerinin ilkelerine dayanmaktadır ve aşağıdaki temel adımları içerir: ses işleme ve özellik çıkarma için hazır veri kümelerini kullanma, dalga formlarını mel spektrogramlarına dönüştürme ve gerektiğinde veri kümelerini hazırlama ve genişletme. Daha sonra akor tanımada yüksek doğruluk elde etmek için çeşitli evrişimli sinir ağı (CNN) mimarileri gibi derin öğrenme modellerini eğitiyor ve optimize ediyorum. İleri teknolojileri kullanarak ve ömür boyu öğrenme ilkelerine bağlı kalarak, araştırmamız bireylerin yaşamları boyunca müzik yolculuğunu geliştirmeyi, hem kişisel zenginleşmeye hem de bilişsel refaha katkıda bulunmayı hedefliyor.

Anahtar Kelimeler

• yaşam boyu müzik eğitimi
• ses işleme
• makine öğrenimi
• yetişkin öğrenciler
• yapay zeka

Real-time chord identification application: Enabling lifelong music education through seamless integration of audio processing and machine learning

Öz

Lifelong music education is critical need for all with a particular focus on adult learners and seniors. One of the difficulties in music education is identifying chords accurately. This is a preliminary study to develop a chord identification application using Artificial Intelligence (AI) technologies. I seek to answer the key research question of how audio processing algorithms and deep learning models can be used to provide real-time, accurate and user-friendly chord recognition that meets the diverse needs of adult learners and senior citizens. Our overall goal is to create an application that not only assists with chord identification, but also fosters a lifelong love of music and learning. My methodology is based on the principles of adult and senior education initiatives and includes the following key steps: using ready-made datasets for audio processing and feature extraction, transforming waveforms into mel spectrograms, and preparing and extending the datasets where necessary. I then train and optimise deep learning models, such as various convolutional neural network (CNN) architectures, to achieve high accuracy in chord recognition. By using advanced technologies and adhering to the principles of lifelong learning, our research aims to enhance the musical journey of individuals throughout their lives, contributing to both personal enrichment and cognitive well-being.

Anahtar Kelimeler

• lifelong music education
• audio processing
• machine learning
• adult learners
• artificial intelligence

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