Analiza in iskanje podobnosti med avdio podpisi zvočnih posnetkov

Patačko Koderman, Žiga (author), Pesek, Matevž (mentor), Marolt, Matija (comentor)

Namen diplomskega dela je razvoj sistema za avdio podpisovanje in razpoznavo posnetkov glasbe. Avdio podpisovanje se uporablja za primerjavo zvočnih posnetkov in je bolj ali manj odporno na šum ter druge motnje iz okolja. V okviru diplomskega dela smo raziskali obstoječe sisteme za avdio podpisovanje, podrobno opisali razviti sistem ter ga evalvirali. Z njim smo indeksirali 900 glasbenih del (54 ur posnetkov) in izmerili njegovo točnost razpoznave glasbe, hitrost indeksiranja, hitrost razpoznave posnetkov ter prostorsko zahtevnost. Sistem je dovolj hiter in točen za uporabo v manjših aplikacijah, kot sta deduplikacija arhivskih posnetkov in razpoznava glasbe, predvajane po radiu. Sistem pričakovano dosega slabše rezultate pri razpoznavi glasbe, posnete v živo, zato za tovrstno uporabo ni primeren.

• Language: Slovenian
• Keywords: razpoznava glasbe, avdio podpisovanje, vektorska podatkovna baza, spektrogram
• Work type: Bachelor thesis/paper
• Typology: 2.11 - Undergraduate Thesis
• Organization: FRI - Faculty of Computer and Information Science
• Year: 2022
• PID: 20.500.12556/RUL-140030
• COBISS.SI-ID: 122827523
• Publication date in RUL: 09.09.2022

Secondary language

• Language: English
• Title: Analysis and similarity comparison between signatures of audio recordings

Abstract

This thesis aims to develop a system for audio fingerprinting and recognition of recorded music. Audio fingerprinting is a process used to compare audio recordings regardless of noise or other environmental factors. Throughout this work, we explore several audio fingerprinting methods and provide a detailed description of the developed system. The system was used to index 900 songs (54 hours of recorded music) and evaluate its accuracy, indexing speed, query speed, and spatial consumption. The system is found to be sufficiently fast and accurate for use in smaller applications like archive deduplication and recognition of songs played over the radio. However, it lacks sufficient accuracy to be used to identify music played in noisy environments.

• Keywords: recognition of music, audio fingerprinting, vector database, spectrogram