Name: Music Emotion Recognition (en Inglés)
Price: 127420.00 CLP
Availability: InStock
Author: Yang, Yi-Hsuan ; Chen, Homer H.
ISBN: 9781439850466

portada Music Emotion Recognition (en Inglés)

Formato

Libro Físico

Autor

Yi-Hsuan Yang

Homer H. Chen

Editorial

CRC Press

Año

2011

Idioma

Inglés

N° páginas

262

Encuadernación

Tapa Dura

Dimensiones

21.1 x 13.7 x 1.5 cm

Peso

0.25 kg.

ISBN13

9781439850466

Categorías

Música
Internet: obras generales
Data mining: minería de datos

Music Emotion Recognition (en Inglés)

Yi-Hsuan Yang (Autor) · Homer H. Chen (Autor) · CRC Press · Tapa Dura

Libro Físico

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Reseña del libro "Music Emotion Recognition (en Inglés)"

Providing a complete review of existing work in music emotion developed in psychology and engineering, Music Emotion Recognition explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems. Among the first publications dedicated to automatic MER, it begins with a comprehensive introduction to the essential aspects of MER--including background, key techniques, and applications.This ground-breaking reference examines emotion from a dimensional perspective. It defines emotions in music as points in a 2D plane in terms of two of the most fundamental emotion dimensions according to psychologists--valence and arousal. The authors present a computational framework that generalizes emotion recognition from the categorical domain to real-valued 2D space. They also: Introduce novel emotion-based music retrieval and organization methods Describe a ranking-base emotion annotation and model training method Present methods that integrate information extracted from lyrics, chord sequence, and genre metadata for improved accuracy Consider an emotion-based music retrieval system that is particularly useful for mobile devices The book details techniques for addressing the issues related to: the ambiguity and granularity of emotion description, heavy cognitive load of emotion annotation, subjectivity of emotion perception, and the semantic gap between low-level audio signal and high-level emotion perception. Complete with more than 360 useful references, 12 example MATLAB(R) codes, and a listing of key abbreviations and acronyms, this cutting-edge guide supplies the technical understanding and tools needed to develop your own automatic MER system based on the automatic recognition model.