# Difference between revisions of "CEFT"

m (→CEFT: expand acronym once on this page...) |
Martin.leese (talk | contribs) m (Promoted everything up a level heading (Level 1 is the page title)) |
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− | = Constrained-Energy Fourier | + | == Constrained-Energy Fourier Transforms == |

− | == Problems with current implementation and possible solutions == | + | === Problems with current implementation and possible solutions === |

− | === Overlapped FFT not critically sampled === | + | ==== Overlapped FFT not critically sampled ==== |

In the current implementation, we encode 4/3 times more samples than necessary because we use 256-point FFTs with 64 samples overlap. | In the current implementation, we encode 4/3 times more samples than necessary because we use 256-point FFTs with 64 samples overlap. | ||

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* Do extrapolation on the input and use a wider FFT. Then optimise the search only for the "real" samples | * Do extrapolation on the input and use a wider FFT. Then optimise the search only for the "real" samples | ||

− | === Non-harmonic signals (i.e. music) === | + | ==== Non-harmonic signals (i.e. music) ==== |

CEFT only works on speech because most of its coding efficiency is provided by the pitch predictor. | CEFT only works on speech because most of its coding efficiency is provided by the pitch predictor. | ||

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* Use two (or more) pitch periods at the same time and use energy conservation to keep everything stable. | * Use two (or more) pitch periods at the same time and use energy conservation to keep everything stable. | ||

− | === Sparse spectrum === | + | ==== Sparse spectrum ==== |

CEFT tends to have musical noise, especially at high frequency when there are very few bits/bin. | CEFT tends to have musical noise, especially at high frequency when there are very few bits/bin. |

## Revision as of 09:03, 23 August 2015

## Contents

## Constrained-Energy Fourier Transforms

### Problems with current implementation and possible solutions

#### Overlapped FFT not critically sampled

In the current implementation, we encode 4/3 times more samples than necessary because we use 256-point FFTs with 64 samples overlap.

Ideas:

- Use an MDCT instead of the FFT
- Do extrapolation on the input and use a wider FFT. Then optimise the search only for the "real" samples

#### Non-harmonic signals (i.e. music)

CEFT only works on speech because most of its coding efficiency is provided by the pitch predictor.

Ideas:

- Sinusoidal prediction
- Use two (or more) pitch periods and choose one for each bin/band/whatever
- Use two (or more) pitch periods at the same time and use energy conservation to keep everything stable.

#### Sparse spectrum

CEFT tends to have musical noise, especially at high frequency when there are very few bits/bin.

Ideas:

- Use a "rotation matrix"
- Prediction from lower frequencies