Skip to main content
  • Home
  • Development
  • Documentation
  • Donate
  • Operational login
  • Browse the archive

swh logo
SoftwareHeritage
Software
Heritage
Archive
Features
  • Search

  • Downloads

  • Save code now

  • Add forge now

  • Help

Raw File Download

To reference or cite the objects present in the Software Heritage archive, permalinks based on SoftWare Hash IDentifiers (SWHIDs) must be used.
Select below a type of object currently browsed in order to display its associated SWHID and permalink.

  • content
content badge
swh:1:cnt:4d04d80546f20c7bac7351facc02672f3d945ac0

This interface enables to generate software citations, provided that the root directory of browsed objects contains a citation.cff or codemeta.json file.
Select below a type of object currently browsed in order to generate citations for them.

  • content
Generate software citation in BibTex format (requires biblatex-software package)
Generating citation ...
{
  "supported_model_type": [
    "GANVocoder",
    "Fastspeech2",
    "DiffSVC",
    "Transformer",
    "EDM",
    "CD"
  ],
  "task_type": "",
  "dataset": [],
  "use_custom_dataset": false,
  "preprocess": {
    // trim audio silence
    "data_augment": false,
    "trim_silence": false,
    "num_silent_frames": 8,
    "trim_fft_size": 512, // fft size used in trimming
    "trim_hop_size": 128, // hop size used in trimming
    "trim_top_db": 30, // top db used in trimming sensitive to each dataset
    // acoustic features
    "extract_mel": false,
    "mel_extract_mode": "",
    "extract_linear_spec": false,
    "extract_mcep": false,
    "extract_pitch": false,
    "pitch_remove_outlier": false,
    "extract_uv": false,
    "pitch_norm": false,
    "extract_audio": false,
    "extract_label": false,
    "pitch_extractor": "parselmouth", // pyin, dio, pyworld, pyreaper, parselmouth, CWT (Continuous Wavelet Transform)
    "extract_energy": false,
    "energy_remove_outlier": false,
    "energy_norm": false,
    "energy_extract_mode": "from_mel",
    "extract_duration": false,
    "extract_amplitude_phase": false,
    "mel_min_max_norm": false,
    // content features
    "use_text": false,
    "use_phone": false,
    "lexicon_path": "./text/lexicon/librispeech-lexicon.txt",
    "extract_whisper_feature": false,
    "extract_contentvec_feature": false,
    "extract_mert_feature": false,
    "extract_wenet_feature": false,
    // Settings for data preprocessing
    "n_mel": 80,
    "win_size": 480,
    "hop_size": 120,
    "sample_rate": 24000,
    "n_fft": 1024,
    "fmin": 0,
    "fmax": 12000,
    "min_level_db": -115,
    "ref_level_db": 20,
    "bits": 8,
    // Directory names of processed data or extracted features
    "processed_dir": "processed_data",
    "trimmed_wav_dir": "trimmed_wavs", // directory name of silence trimed wav
    "raw_data": "raw_data",
    "wav_dir": "wavs", // directory name of processed wav (such as downsampled waveform)
    "audio_dir": "audios",
    "log_amplitude_dir": "log_amplitudes",
    "phase_dir": "phases",
    "real_dir": "reals",
    "imaginary_dir": "imaginarys",
    "label_dir": "labels",
    "linear_dir": "linears",
    "mel_dir": "mels", // directory name of extraced mel features
    "mcep_dir": "mcep", // directory name of extraced mcep features
    "dur_dir": "durs",
    "lab_dir": "labs", // directory name of extraced label features
    "wenet_dir": "wenet", // directory name of extraced wenet features
    "contentvec_dir": "contentvec", // directory name of extraced wenet features
    "pitch_dir": "pitches", // directory name of extraced pitch features
    "energy_dir": "energys", // directory name of extracted energy features
    "phone_pitch_dir": "phone_pitches", // directory name of extraced pitch features
    "phone_energy_dir": "phone_energys", // directory name of extracted energy features
    "uv_dir": "uvs", // directory name of extracted unvoiced features
    "duration_dir": "duration", // ground-truth duration file
    "phone_seq_file": "phone_seq_file", // phoneme sequence file
    "file_lst": "file.lst",
    "train_file": "train.json", // training set, the json file contains detailed information about the dataset, including dataset name, utterance id, duration of the utterance
    "valid_file": "test.json", // validattion set
    "spk2id": "spk2id.json", // used for multi-speaker dataset
    "utt2spk": "utt2spk", // used for multi-speaker dataset
    "emo2id": "emo2id.json", // used for multi-emotion dataset
    "utt2emo": "utt2emo", // used for multi-emotion dataset
    // Features used for model training
    "use_phn_seq": false,
    "use_lab": false,
    "use_linear": false,
    "use_mel": false,
    "use_min_max_norm_mel": false,
    "use_wav": false,
    "use_phone_pitch": false,
    "use_log_scale_pitch": false,
    "use_phone_energy": false,
    "use_phone_duration": false,
    "use_log_scale_energy": false,
    "use_wenet": false,
    "use_dur": false,
    "use_spkid": false, // True: use speaker id for multi-speaker dataset
    "use_emoid": false, // True: use emotion id for multi-emotion dataset
    "use_frame_pitch": false,
    "use_uv": false,
    "use_frame_energy": false,
    "use_frame_duration": false,
    "use_audio": false,
    "use_label": false,
    "use_one_hot": false,
    "use_amplitude_phase": false,
    "data_augment": false,
    "align_mel_duration": false
  },
  "train": {
    "ddp": true,
    "random_seed": 970227,
    "batch_size": 16,
    "max_steps": 1000000,
    // Trackers
    "tracker": [
      "tensorboard"
      // "wandb",
      // "cometml",
      // "mlflow",
    ],
    "max_epoch": -1,
    // -1 means no limit
    "save_checkpoint_stride": [
      5,
      20
    ],
    // unit is epoch
    "keep_last": [
      3,
      -1
    ],
    // -1 means infinite, if one number will broadcast
    "run_eval": [
      false,
      true
    ],
    // if one number will broadcast
    // Fix the random seed
    "random_seed": 10086,
    // Optimizer
    "optimizer": "AdamW",
    "adamw": {
      "lr": 4.0e-4
      // nn model lr
    },
    // LR Scheduler
    "scheduler": "ReduceLROnPlateau",
    "reducelronplateau": {
      "factor": 0.8,
      "patience": 10,
      // unit is epoch
      "min_lr": 1.0e-4
    },
    // Batchsampler
    "sampler": {
      "holistic_shuffle": true,
      "drop_last": true
    },
    // Dataloader
    "dataloader": {
      "num_worker": 32,
      "pin_memory": true
    },
    "gradient_accumulation_step": 1,
    "total_training_steps": 50000,
    "save_summary_steps": 500,
    "save_checkpoints_steps": 10000,
    "valid_interval": 10000,
    "keep_checkpoint_max": 5,
    "multi_speaker_training": false, // True: train multi-speaker model; False: training single-speaker model;
    "gradient_accumulation_step": 1,
    "max_epoch": -1,
    // -1 means no limit
    "save_checkpoint_stride": [
      5,
      20
    ],
    // unit is epoch
    "keep_last": [
      3,
      -1
    ],
    // -1 means infinite, if one number will broadcast
    "run_eval": [
      false,
      true
    ],
    // Batchsampler
    "sampler": {
      "holistic_shuffle": true,
      "drop_last": true
    },
    // Dataloader
    "dataloader": {
      "num_worker": 32,
      "pin_memory": true
    },
    // Trackers
    "tracker": [
      "tensorboard"
      // "wandb",
      // "cometml",
      // "mlflow",
    ],
  },
}

back to top

Software Heritage — Copyright (C) 2015–2025, The Software Heritage developers. License: GNU AGPLv3+.
The source code of Software Heritage itself is available on our development forge.
The source code files archived by Software Heritage are available under their own copyright and licenses.
Terms of use: Archive access, API— Content policy— Contact— JavaScript license information— Web API