Name
Title | ||
|---|---|---|
Low-complexity F0-based speech/nonspeech discrimination approach for digital hearing aids |
Abstract | ||
|---|---|---|
Digital hearing aids impose strong complexity and memory constraints on digital signal processing algorithms that implement different applications. This paper proposes a low complexity approach for automatic sound classification in digital hearing aids. The proposed scheme, which operates on a frame-by-frame basis, consists of two stages: analysis stage and classification stage. The analysis stage provides a set of low-complexity signal features derived from fundamental frequency (F0) estimation. Here, F0 estimation is performed by a decimated difference function, which results in a reduced-complexity analysis stage. The classification stage has been designed with the aim of reducing the complexity while maintaining high accuracy rates. Three low-complexity classifiers have been evaluated (tree-based C4.5, 1-Nearest Neighbor (1-NN) and a Multilayer Perceptron (MLP)), the MLP being chosen because it provides the best accuracy rates and fits to the computational and memory constraints of ultra low-power DSP-based hearing aids. The classification stage is composed of a MLP classifier followed by a Hidden Markov Model (HMM), providing a good trade-off solution between complexity and classification accuracy rate. The goal of the proposed approach is to perform a robust discrimination among speech/nonspeech parts of audio signals in commercial digital hearing aids, the computational cost being a critical issue. For the experiments, an audio database including speech, music and noise signals has been used. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/s11042-010-0523-1 | Multimedia Tools Appl. |
Keywords | Field | DocType |
Fundamental frequency estimation,Automatic sound classification,Digital hearing aids,Difference function,Multilayer perceptron,Hidden Markov model | Audio signal,Digital signal processing,Fundamental frequency,Pattern recognition,Computer science,Speech recognition,Sound classification,Multilayer perceptron,Artificial intelligence,Classifier (linguistics),Hidden Markov model,Digital signal processing algorithms | Journal |
Volume | Issue | ISSN |
54 | 2 | 1380-7501 |
Citations | PageRank | References |
3 | 0.43 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pablo Cabañas Molero | 1 | 34 | 4.18 |
| Nicolas Ruiz Reyes | 2 | 11 | 2.30 |
| Pedro Vera Candeas | 3 | 5 | 1.50 |
| Saturnino Maldonado Bascon | 4 | 19 | 1.56 |