Design and Implementation of a Web-Based Software Framework for Real Time Intelligent Audio Coding Based on Speech/Music Discrimination

Garcia Galan S, Muñoz Exposito JE, Ruiz Reyes N, Vera Candeas P. Design and Implementation of a Web-Based Software Framework for Real Time Intelligent Audio Coding Based on Speech/Music Discrimination. In: AES Convention 122. Audio Engineering Society; 2007. Paper 7005. Available from: https://aes.org/publications/elibrary-page/?id=13990

@inproceedings{GarciaGalan2007_13990,
  author = {Garcia Galan, Sebastian and Muñoz Exposito, Jose Enrique and Ruiz Reyes, Nicolas and Vera Candeas, Pedro},
  title = {{Design and Implementation of a Web-Based Software Framework for Real Time Intelligent Audio Coding Based on Speech/Music Discrimination}},
  booktitle = {AES Convention 122},
  note = {Paper 7005},
  year = {2007},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=13990}
}

TY  - CPAPER
TI  - Design and Implementation of a Web-Based Software Framework for Real Time Intelligent Audio Coding Based on Speech/Music Discrimination
AU  - Garcia Galan, Sebastian
AU  - Muñoz Exposito, Jose Enrique
AU  - Ruiz Reyes, Nicolas
AU  - Vera Candeas, Pedro
T2  - AES Convention 122
M1  - Paper 7005
PY  - 2007
DA  - 2007/05/06
UR  - https://aes.org/publications/elibrary-page/?id=13990
PB  - Audio Engineering Society
LA  - en
AB  - In this work a software framework based on client-server architecture is implemented for real time intelligent audio coding. A speech/music discrimination scheme analyzes the input audio signal and takes a decision about the nature of the audio signal (speech or music) on a frame by frame basis. According to the decision of the speech/music discriminator, a suitable coder is selected at each frame. The designed software framework makes use of the speech and audio coders incorporated into the MPEG4 audio standard (HVXC or CELP for speech frames and TwinVQ or AAC for music frames) to evaluate the performance of an intelligent multi-mode audio coder. The framework supports several types of audio features (timbral texture features and rhythmic content features) and classifiers (classical Statistical Pattern Recognition (SPR) classifiers, Multilayer Perceptron Neural Networks (MLPNN), Support Vector Machines (SVM), Fuzzy Expert Systems (FES), Hidden Markov Models (HMM)). Comparison between a speech/music discrimination based-intelligent audio coder and MPEG4-AAC has been performed using audio signals representative of the two corresponding classes (speech and music). Subjective and objective tests have been accomplished aiming at assessing the behaviour of the intelligent audio coding scheme.
ER  -