Czasopismo | ELEKTRONIKA - KONSTRUKCJE, TECHNOLOGIE, ZASTOSOWANIA | Rocznik 2011 - zeszyt 10

Analyzing feature trajectories for audio content discrimination

Tomasz Mąka

nr katalogowy: 63268

The field of audio information indexing and retrieval needs audio analysis tasks like segmentation and classification. Its growing popularity and numerous applications are connected with the availability of huge audio resources on the Internet. The large variability of audio content in such resources has direct influence on effectiveness and usability of audio management systems. Audio data categorization or searching by listening seems to be difficult task, thus automatic and effective mechanism is required to explore data. Typical audio retrieval system involves three steps: segmentation, feature extraction and classification. The final efficiency is dependent on all these steps and audio acquisition environment. Segmentation and classification processes are performed on the features variability basis, thus the choice of audio features set with good discrimination properties is important. It is still difficult to decide how big should be feature set and what kind of features should be selected. Therefore, to determine set of audio features for selected number of classes the feature selection step is introduced in audio analysis systems. The type of source audio data determines the specificity of classification stage. The most common audio classification task is to determine speech regions in input signal. In such case, the binary discrimination between speech and non-speech parts is performed. Automatic systems for audio classification usually categorize sound segments into several groups. For example, in broadcast news material, determination between speech and music is executed at first stage. At subsequent stages, an analysis of mixtures (speech with background music or environmental noise) and specific signals (silence, noise) is often considered. Audio segmentation as the first process performed in automatic systems for audio classification is mostly based on Bayesian Information Criterion (BIC) se[...]

Jeśli masz wykupiony/przyznany dostęp - zaloguj się. Skorzystaj z naszych propozycji zakupu!

Publikacja


e-Publikacja (format pdf) - nr 25237 "Simatic WinCC V6.2 z funk..." licencja: Osobista Produkt cyfrowy	10.00 zł

Zeszyt


MASZYNY, TECHNOLOGIE, MATERIAŁY - TECHNIKA ZAGRANICZNA - e-zeszyt (pdf) 2007-2 licencja: Osobista Produkt cyfrowy	12.96 zł

Zeszyt

2011-10

Twój Koszyk

Publikacja

Zeszyt

Zeszyt

Czasopisma