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Bob 2.0 extraction of cepstral features (MFCC or LFCC) from audio

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 |
---|---|---|

speech | system/array_1d_floats/1 | Input |

vad | system/array_1d_integers/1 | Input |

features | system/array_2d_floats/1 | Output |

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

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

f_max | Max frequency of the range used in bandpass filtering | float64 | 8000.0 | |

delta_win | Window size used in delta and delta-delta computation | uint32 | 2 | |

withDelta | Compute deltas (with window size specified by delta_win) | bool | True | |

pre_emphasis_coef | Pre-emphasis coefficient | float64 | 0.95 | |

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 | |

dct_norm | Use normalized DCT | bool | False | |

normalizeFeatures | Normalize computed Cepstral features (shift by mean and divide by std) | bool | True | |

filter_frames | Filter frames with computed Cepstral features based on the VAD labels. Either trim out silence head/tails, keep only speech, or keep only silence. | string | trim_silence | trim_silence, silence_only, speech_only |

rate | Sampling rate of the speech signal | float64 | 16000.0 | |

n_filters | Number of filter bands | uint32 | 24 | |

f_min | Min frequency of the range used in bandpass filtering | float64 | 0.0 | |

withDeltaDelta | Compute delta-deltas (with window size specified by delta_win) | bool | True | |

withEnergy | Use power of the FFT magnitude, otherwise just an absolute value of the magnitude | bool | True | |

mel_scale | Set true to use Mel-scaled triangular filter, otherwise it's a linear scale | bool | True | |

n_ceps | Number of cepstral coefficients | uint32 | 19 |

The code for this algorithm in Python

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Extract cepstral features (MFCC or LFCC) from audio

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,avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_antispoofing,avspoof/2@physicalaccess_verify_train_spoof,avspoof/2@physicalaccess_verify_train | pkorshunov/spoof-score-fusion-roc_hist/1 | ||||

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

pkorshunov/pkorshunov/speech-pad-simple/1/speech-pad_gmm-pa | avspoof/2@physicalaccess_antispoofing | pkorshunov/simple_antispoofing_analyzer/4 | ||||

pkorshunov/pkorshunov/isv-speaker-verification-spoof/1/isv-speaker-verification-spoof-pa | avspoof/2@physicalaccess_verification_spoof,avspoof/2@physicalaccess_verification | pkorshunov/eerhter_postperf_iso_spoof/1 | ||||

pkorshunov/pkorshunov/isv-speaker-verification/1/isv-speaker-verification-licit | avspoof/2@physicalaccess_verification | pkorshunov/eerhter_postperf_iso/1 |

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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