Name
Title | ||
|---|---|---|
Feature-Based Language Discrimination in Radio Productions via Artificial Neural Training. |
Abstract | ||
|---|---|---|
The current paper focuses on the discrimination of audio content, deriving from radio productions, based on the spoken language. During the implementation several audio features were extracted and subsequently evaluated, containing the spectral, timbre and tempo properties of the implicated voice signals. In this process, the differentiated patterns that appear in radio productions, such as speech signals, phone conversations and music interferences had to be initially detected and classified, leading in the employment of a prequel generic classification scheme. The hierarchical structure of discrimination integrated parametric segmentation with various window lengths, in order to detect the most efficient ones. The conducted experiments were supported by machine learning approaches, and more specifically by artificial neural networks topologies, which demonstrate increased discrimination potentials, when they are implicated in audio semantic analysis problems. The achieved overall and partial classification performances were high, revealing the saliency of the selected parameters and the efficiency of the whole implemented methodology. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2814895.2814928 | Audio Mostly Conference |
Keywords | Field | DocType |
Audio Features, Radio, Artificial Neural Networks, Data Mining | Segmentation,Computer science,Salience (neuroscience),Speech recognition,Network topology,Phone,Parametric statistics,Artificial neural network,Timbre,Spoken language | Conference |
Citations | PageRank | References |
1 | 0.35 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| R. Kotsakis | 1 | 36 | 5.76 |
| A. Mislow | 2 | 1 | 0.35 |
| G. Kalliris | 3 | 277 | 14.72 |
| Maria Matsiola | 4 | 4 | 1.75 |