Essays about: "mel spectrogram"

Showing result 1 - 5 of 10 essays containing the words mel spectrogram.

  1. 1. Song Popularity Prediction with Deep Learning : Investigating predictive power of low level audio features

    University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Author : Gustaf Holst; Jan Niia; [2023]
    Keywords : machine learning; deep learning; audio;

    Abstract : Today streaming services are the most popular way to consume music, and with this the field of Music Information Retrieval (MIR) has exploded. Tangy market is a music investment platform and they want to use MIR techniques to estimate the value of not yet released songs. READ MORE

  3. 2. Violin Artist Identification by Analyzing Raga-vistaram Audio

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Nandakishor Ramlal; [2023]
    Keywords : Artist identification; Music information retrieval; Deep Learning; Convolutional Neural Network; Convolutional Recurrent Neural Network; Embeddings; log-Melspectrogram; Artistidentifiering; återhämtning av musikinformation; Deep Learning; Convolutional Neural Network; Convolutional Recurrent Neural Network; Inbäddningar; log-Melspektrogram;

    Abstract : With the inception of music streaming and media content delivery platforms, there has been a tremendous increase in the music available on the internet and the metadata associated with it. In this study, we address the problem of violin artist identification, which tries to classify the performing artist based on the learned features. READ MORE

  4. 3. Estimating the risk of insurance fraud based on tonal analysis

    University essay from Lunds universitet/Matematisk statistik

    Author : Henrik Steneld; [2022]
    Keywords : Spectral analysis; Speaker recognition; Tonal analysis; Speaker Diarization; Machine Learning; LSTM; ResNet; Fraud detection; Mathematics and Statistics;

    Abstract : Insurance companies utilize various methods for identifying claims that are of potential fraudulent nature. With the ever progressing field of artificial intelligence and machine learning models, great interest can be found within the industry to evaluate the use of new methods that may arise as a result of new advanced models in combination with the rich data that is being gathered. READ MORE

  5. 4. Towards a Nuanced Evaluation of Voice Activity Detection Systems : An Examination of Metrics, Sampling Rates and Noise with Deep Learning

    University essay from Linköpings universitet/Institutionen för datavetenskap

    Author : Ludvig Joborn; Mattias Beming; [2022]
    Keywords : voice activity detection; VAD; deep learning; machine learning; ML; artificial intelligence; AI; convolutional neural network; CNN; deep neural network; DNN; sound event detection; SED; mel spectrogram; audio processing; polyphonic sound detection score; PSDS; signal processing; signal to noise ratio; SNR; recurrent convolutional residual neural network; RCRNN; sampling rate; Gaussian noise;

    Abstract : Recently, Deep Learning has revolutionized many fields, where one such area is Voice Activity Detection (VAD). This is of great interest to sectors of society concerned with detecting speech in sound signals. One such sector is the police, where criminal investigations regularly involve analysis of audio material. READ MORE

  6. 5. Multi-objective optimization for model selection in music classification

    University essay from KTH/Optimeringslära och systemteori

    Author : Rintaro Ujihara; [2021]
    Keywords : Music emotion recognition; Mel spectrogram; MFCC; CENS; Onset; Tonnetz; HPSS; 1D convolutional neural network; Attention LSTM; 1DCNN BiLSTM; Pareto optimality;

    Abstract : With the breakthrough of machine learning techniques, the research concerning music emotion classification has been getting notable progress combining various audio features and state-of-the-art machine learning models. Still, it is known that the way to preprocess music samples and to choose which machine classification algorithm to use depends on data sets and the objective of each project work. READ MORE