Summary of the paper
| Title | Modified LTSE-VAD Algorithm for Applications Requiring Reduced Silence Frame Misclassification |
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| Authors | Iker Luengo, Eva Navas, Igor Odriozola, Ibon Saratxaga, Inmaculada Hernaez, Iñaki Sainz and Daniel Erro |
| Abstract | The LTSE-VAD is one of the best known algorithms for voice activity detection. In this paper we present a modified version of this algorithm, that makes the VAD decision not taking into account account the estimated background noise level, but the signal to noise ratio (SNR). This makes the algorithm robust not only to noise level changes, but also to signal level changes. We compare the modified algorithm with the original one, and with three other standard VAD systems. The results show that the modified version gets the lowest silence misclassification rate, while maintaining a reasonably low speech misclassification rate. As a result, this algorithm is more suitable for identification tasks, such as speaker or emotion recognition, where silence misclassification can be very harmful. A series of automatic emotion identification experiments are also carried out, proving that the modified version of the algorithm helps increasing the correct emotion classification rate. |
| Topics | Tools, systems, applications, Prosody, Emotion Recognition/Generation |
Full paper |
Modified LTSE-VAD Algorithm for Applications Requiring Reduced Silence Frame Misclassification |
Slides |
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| Bibtex | @InProceedings{LUENGO10.741, author = {Iker Luengo and Eva Navas and Igor Odriozola and Ibon Saratxaga and Inmaculada Hernaez and Iñaki Sainz and Daniel Erro}, title = {Modified LTSE-VAD Algorithm for Applications Requiring Reduced Silence Frame Misclassification}, booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |