Efficient voice activity detection algorithms using long-term speech information
By J. Ramírez, José C. Segura, C. Benítez, A. de la Torre, Antonio J. Rubio. Speech Communication, 2004
467 citations recorded by the source corpus.
Subfields: Computational Mechanics, Signal Processing
View Paper: https://www.semanticscholar.org/paper/4749600daf5ff8c4ff75cd0f02f010addb28c2ff
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
- Björn Schuller
- Israel Cohen
- Felix Weninger
- P. Loizou
- Junichi Yamagishi
- Cassia Valentini-Botinhao
- Chin-Hui Lee
- Jun Du
In Signal Processing
- Björn Schuller
- Florian Eyben
- Felix Weninger
- Israel Cohen
- Ido Ariav
- Maja Pantic
- Soujanya Poria
- Erik Cambria
Citations in the corpus
- Real-life voice activity detection with LSTM Recurrent Neural Networks and an application to Hollywood movies (2013, methodology): “The algorithm proposed in [6], as the one in [8], is based on the concept that more consecutive speech frames concur into the definition of the LR function.”
- An End-to-End Multimodal Voice Activity Detection Using WaveNet Encoder and Residual Networks (2019, methodology): “More advanced methods are model-based methods that focus on estimating a statistical model for the noisy signal [4]–[7].”