Abstract
This paper describes a novel GMM-based bandwidth extension (BWE) method based on a sub-band basis spectrum model (SBM), in which each dimensional component represents a specific acoustic space in the frequency domain. The proposed method can achieve the BWE from a speech data with an arbitrary frequency bandwidth while the conventional methods perform the conversion from a fixed narrowband data. In the proposed method, we train a GMM with SBM parameters extracted from wideband spectra in advance. An input signal with a limited frequency band is converted into a wideband signal by estimating high-band SBM components from low-band SBM components of the input signal based on the GMM. The results of some objective and subjective evaluations show that the proposed method extends bandwidth of speech data robustly.
| Original language | English |
|---|---|
| Pages (from-to) | 2489-2493 |
| Number of pages | 5 |
| Journal | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH |
| Publication status | Published - 2014 |
| Externally published | Yes |
| Event | 15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014 - Singapore, Singapore Duration: 2014 Sept 14 → 2014 Sept 18 |
Keywords
- Bandwidth extension
- Gaussian mixture model
- Speech synthesis
- Sub-band basis spectrum model
- Voice conversion
ASJC Scopus subject areas
- Language and Linguistics
- Human-Computer Interaction
- Signal Processing
- Software
- Modelling and Simulation