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Bob 2.0 LBP histograms of spectrogram bands plus bands-ratio.

This algorithm is a **legacy** one. The API has changed since its implementation. New versions and forks will need to be updated.

This algorithm is **splittable**

Algorithms have at least one
**input** and one **output**. All
algorithm endpoints are organized in **groups**.
Groups are used by the platform to indicate which inputs and
outputs are synchronized together. The first group is
automatically synchronized with the channel defined by the
block in which the algorithm is deployed.

Endpoint Name | Data Format | Nature |
---|---|---|

labels | system/array_1d_integers/1 | Input |

speech | system/array_1d_floats/1 | Input |

features | system/array_1d_floats/1 | Output |

Parameters allow users to change the configuration of an algorithm when scheduling an experiment

Name | Description | Type | Default | Range/Choices |
---|---|---|---|---|

mel_scale | Apply Mel-scale filtering or use linear (default - linear) | bool | True | |

pre_emphasis_coef | Pre-emphasis coefficient, used in the spectrogram computation | float64 | 1.0 | |

f_max | Maximum frequency of the spectrogram | float64 | 4000.0 | |

lbp_to_average | LBP parameter. Compare the pixels to the center pixel or to the average | bool | False | |

win_shift_ms | The length of the overlap between neighboring windows. Typically the half of window length. | float64 | 10.0 | |

win_length_ms | The length of the sliding processing window, typically about 20 ms | float64 | 20.0 | |

n_lbp_histograms | Split resulted spectrogram in the number of bands and compute LBP histogram for each | uint32 | 2 | |

rate | Sampling rate of the speech signal | float64 | 16000.0 | [2000.0, 256000.0] |

n_filters | The number of filter bands used in spectrogram computation | uint32 | 40 | |

lbp_circular | LBP parameter. Extract neighbors on a circle or on a square? | bool | True | |

lbp_radius | LBP parameter. The radius of the LBP in both vertical and horizontal direction together | uint32 | 1 | [1, 10] |

lbp_neighbors | LBP parameter. Number of neighbors | uint32 | 8 | 4, 8, 16 |

lbp_uniform | LBP parameter. Only uniform LBP codes (with less than two bit-changes between 0 and 1) are considered; all other strings are combined into one LBP code | bool | False | |

lbp_elbp_type | LBP parameter. How to generate the bit strings from the pixels: regular - Choose one bit for each comparison of the neighboring pixel with the central pixel; transitional - Compare only the neighboring pixels and skip the central one; direction-coded - Compute a 2-bit code for four directions. | string | regular | regular, transitional, direction-coded |

The code for this algorithm in Python

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Silent start and end of a sample are trimmed using Voice Activity Detection (VAD) labels as input.

Updated | Name | Databases/Protocols | Analyzers | |||
---|---|---|---|---|---|---|

pkorshunov/pkorshunov/isv-asv-pad-fusion-complete/1/asv_isv-pad_lbp_hist_ratios_lr-fusion_lr-pa_aligned | avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_verify_train_spoof,avspoof/2@physicalaccess_verification,avspoof/2@physicalaccess_antispoofing,avspoof/2@physicalaccess_verify_train | pkorshunov/spoof-score-fusion-roc_hist/1 | ||||

pkorshunov/pkorshunov/speech-pad-simple/1/speech-pad_lbp_hist_ratios_lr-pa_aligned | avspoof/2@physicalaccess_antispoofing | pkorshunov/simple_antispoofing_analyzer/4 |

This table shows the number of times this algorithm
has been **successfully** run using the given environment. Note
this does not provide sufficient information to evaluate if the
algorithm will run when submitted to different conditions.

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