en_US.yaml

lang_code: "English (US)"
app_ttl: "DiffTrainer"
tab_ttl_1: "About"
tab_ttl_2: "Data Preparation"
tab_ttl_3: "Configuration"
tab_ttl_4: "Binarize&Train"
tab_ttl_5: "Export Singer(basic)"
tab_ttl_6: "Export Singer(advanced)"


# About tab
vers: "version"
changelog: "View changelog"
update: "Update tools"
update2: "Installs DiffSinger and SOME, but not the Python requirements.\n Running this a second time will delete and replace all files."
update_available1: "Update Available"
update_available2: "Updates to DiffSinger are available! \nNecessary files already exist. Do you want to re-download and replace them? Make sure any user files are backed up OUTSIDE of the DiffSinger folder."
update_not_available1: "No Update Available"
update_not_available2: "You have the latest officially supported version of DiffSinger. \nNecessary files already exist. Do you want to re-download and replace them? Make sure any user files are backed up OUTSIDE of the DiffSinger folder."
setup_completo1: "DiffSinger Tools Installed"
setup_completo2: "DiffTrainer is now ready for use."
cred_lead: "Maintainer:"
cred_tools: "Additional credits"
cred_trans: "Translation: N/A" #translators: your username here
lang_sel: "Select language:" #note: string should not be longer than this or it will be cut off

#Data Prep tab
seg: "Segment data"
seg2: "Uses MLo7's corpus_segmenter to cut data into smaller sections."
length_seg: "Preferred length of segments(seconds)"
length_seg2: "How long each segment is allowed to be. Longer segments will be split.\nThis is not an exact value, and may be shorter or longer if needed.\nRecommended value: At least 5, but very weak GPUs may only be able to handle 2-4. 1 is not recommended."
estmidi: "Estimate MIDI"
estmidi2: "Calculates pitch of each phoneme. Required to train a pitch model."
rawdata: "Select raw data folder"
rawdata2: "Can be either a single folder containing both .wav and .lab files, \nor a folder with subfolders for different speakers."
prepdata: "Prepare data"
prepdata2: "Run the process to prepare the data in Diffsinger format."
segdone1: "DiffTrainer: Conversion Complete"
segdone2: "Your data is now ready for use with DiffSinger."

#Config tab
type: "Type:"
aco: "Acoustic"
var: "Variance"
adv: "ADVANCED: Custom config"
adv2: "Unlocks options to individually select parameters. \nOnly recommended for experienced users."
advtoggle: "Toggling advanced configuration"
datafolder: "Select formatted data folder"
datafolder2: "Select a folder that has been processed on the previous tab. \nCan be located anywhere, but a subfolder of /diffsinger/data is recommended."
savefolder: "Select checkpoint save folder"
savefolder2: "Select where your checkpoints will be saved. Must be a subfolder of /DiffSinger/checkpoints."
confsel: "Select configuration:"
confsel2: "Select from this list of preset configurations.\n All options have been tested."
selected: "Configuration selected:"
advconfig: "Advanced configuration:"
advconfig2: "Select individual options for the configuration.\n Non-functional combinations are possible."
preseterror: "Please select a preset or enable custom configuration!"
stretch: "Stretch embed is only recommended for acoustic."
vr: "VR preprocessing"
vr2: "Can produce more accurate variance results, but requires high processing power. \n Only recommended for GPU users."
backbone: "Backbone selection"
speaker: "Speaker"
spk_lang: "Language"
spk_lang2: "The primary language of the speaker."
spk_id: "ID"
spk_id2: "All speakers with the same number will export as a single, merged speaker.\nRecommended for multiple languages from the same voice."
lang_edit: "Edit language settings"
lang_edit2: "Configure which dictionaries are imported, global phonemes, and merged phonemes."
saveint: "Save interval:"
saveint2: "The checkpoint will save every x steps."
maxbatch: "Max batch size"
maxbatch2: "How many files the training will process at once.\nRecommended values vary heavily by system, but try starting with 9 for acoustic and 24 for variance.\nThis value can be changed without reprocessing the binaries."
saveconf: "Save configuration"
sampleerror: "Not enough samples in" #as in not enough samples in spk_name
input: "Input"

dicts: "Dictionaries:"
dicts2: "Make sure to list only the dictionaries for languages being used. \nSelect a dictionary to remove by clicking the line to highlight it."
add_dict: "Add dictionary"
del_dict: "Remove dictionary"
enterdict1: "Enter the language code:"
enterdict2: "Enter the filepath for the new dictionary:"
ext_ph: "Extra phonemes:"
ext_ph2: "List all global phonemes with no prefix, or additional language-specific phonemes with their prefix. \nSeparate phonemes with commas, spaces are optional."
merge: "Merge list location:"
merge2: "Writing your own merged phoneme list is extremely recommended. \nThe default list provided should mostly be taken as a reference for formatting. \nThis file must be located in the dictionaries folder."
langsave: "Save and return to configuration"

#Train tab
step1: "Select configuration"
step1-2: "Select a configuration that has been set up for the correct dataset."
step2: "Select checkpoint folder"
step2-2: "Select the folder where checkpoints will be saved.\nThis should match the one in the configuration."
step3a: "Binarize data"
step3a2: "Prepares data for the training process.\nRun this once per configuration."
step3b: "Train"
statusheader: "Status:"
status1: "Idle"
binstatus2: "Binarizing(see terminal for progress)"
trainstatus2: "Training(see terminal for progress)"
binstatus3: "Binarization complete!"
trainstatus3: "Training complete!"
binstatus4: "Binarization ended early"
trainstatus4: "Training ended early"
status5: "Stopped due to error(see terminal)"
status6: "Stopping..."
patchlabel: "Optional patch:"
patchbutton: "Use Tensor cores"
patchtip: "If you get a message about using tensor cores at the beginning of training, this patch may improve performance slightly. Apply once after each DiffSinger update."
binarydone1: "DiffTrainer: Preprocessing Complete"
binarydone2: "Your data is now ready for training."
binaryerror1: "DiffTrainer: Error Preprocessing"
generalerror2: "See terminal window for details."
traindone1: "DiffTrainer: Training Complete"
traindone2: "Maximum steps reached!"
trainerror1: "DiffTrainer: Error Training"

#Export tab
##strings 'aco', 'var', and 'step2' are reused
acotip: "Exports an acoustic checkpoint to ONNX."
vartip: "Exports a variance checkpoint to ONNX."
step2-2alt: "Select the folder where checkpoints have been saved.\nThe most recent checkpoint in the folder will be used."
dropspk: "OPTIONAL: Drop speakers"
onnx: "Export ONNX"
onnxerror: "Wavenet requires Torch 1.13.x to export. \nPlease switch environments and try again."
namebox: "Enter the name of your singer with no spaces or special characters."
getaco: "Select acoustic checkpoint folder"
getaco2: "This should be the same folder used for saving checkpoints, NOT the onnx folder."
getvar: "Select variance checkpoint folder"
dur: "Duration"
pit: "Pitch"
ousave: "Select save location"
ousave2: "Select where the final singer folder will be saved.\nIt is recommended to save directly into your OpenUTAU/singers folder."
vocoder: "OPTIONAL: Custom vocoder"
vocoder_adv: "Vocoder ONNX"
vocoder2: "If the model has a non-default vocoder, select the ONNX file here."
dsdict: "Generate base dsdict files"
dsdict2: "Attempts to predict each phoneme's type and write OU-compatible dsdict files. \nNot fully reliable without editing."
ouexport: "Prepare for OpenUtau"

#Quick Inference
##strings 'getaco' and 'getvar' are reused
getds: "Select .ds file"
eval: "Evaluating .ds file..."
hasdur: "Existing duration data detected"
haspitch: "Existing pitch data detected"
hasbre: "Existing breathiness data detected"
hasene: "Existing energy data detected"
hasten: "Existing tension data detected"
hasvoc: "Existing voicing data detected"
eval2: ".ds file evaluated!"
varckpt: "Variance ckpt folder"
acockpt: "Acoustic ckpt folder"
overwrite: "Overwrite existing parameters:"
spk: "enter speaker name"
langcode: "main language code"
inf1: "Inferencing variance data..."
inf2: "Inferencing acoustic data..."
render: "Render audio"
replay: "Replay rendered audio"
replayerror: "Error replaying rendered audio"


#test
testingline: "testtesttest"