From 9bb90df9f710da95ccbb8cd728fedff63fac6256 Mon Sep 17 00:00:00 2001 From: Thorsten Mueller Date: Sat, 22 Aug 2020 12:06:07 +0200 Subject: [PATCH] Update for dataset version 2 --- README.md | 23 ++- models/thorsten-taco2-v0.0.1/Dockerfile | 68 -------- models/thorsten-taco2-v0.0.1/README.md | 3 - models/thorsten-taco2-v0.0.1/config.json | 148 ------------------ .../de-test-sentences.txt | 7 - 5 files changed, 11 insertions(+), 238 deletions(-) delete mode 100644 models/thorsten-taco2-v0.0.1/Dockerfile delete mode 100644 models/thorsten-taco2-v0.0.1/README.md delete mode 100644 models/thorsten-taco2-v0.0.1/config.json delete mode 100644 models/thorsten-taco2-v0.0.1/de-test-sentences.txt diff --git a/README.md b/README.md index ce31339..153af70 100644 --- a/README.md +++ b/README.md @@ -70,23 +70,22 @@ To get an impression what my voice sounds to decide if it fits to your project i > Interested in evolution of this dataset? See following pdf document ([evolution of thorsten dataset](./EvolutionOfThorstenDataset.pdf) ) ## Download information -> * https://drive.google.com/file/d/1yKJM1LAOQpRVojKunD9r8WN_p5KzBxjc/view?usp=sharing -> * Download size: 2,7GB +> Download size: 2,7GB + +Version | Description | Link +------------ | ------------- | ------------- | ------------- +thorsten-de-v01 | Initial version | [Google Drive Download v01](https://drive.google.com/file/d/1yKJM1LAOQpRVojKunD9r8WN_p5KzBxjc/view?usp=sharing) +thorsten-de-v02 | normalized to -24dB and split metadata.csv into shuffeled metadata_train.csv and metadata_val.csv | [Google Drive Download v02](https://drive.google.com/file/d/1mGWfG0s2V2TEg-AI2m85tze1m4pyeM7b/view?usp=sharing) + # Trained tacotron2 model "thorsten" -> Training is currently in progress. +If you trained a model on "thorsten" dataset please file an issue with some information on it. Sharing a trained model is highly appreciated. -> If you trained a model on "thorsten" dataset please file an issue with some information on it. Sharing a trained model is highly appreciated. +## Trained models (TODO) -## Trained models (with at least acceptable) quality -Inside the "models" (sub)folders are configs and Dockerfiles for a specific training from scratch. -> Thanks to @erogol and @repodiac for brining in idea/code for script/container files. - - -Folder | Date | Branch (Mozilla TTS repo) | Description +Folder | Date | Link | Description ------------ | ------------- | ------------- | ------------- -thorsten-taco2-v0.0.1 | august 2020 | dev | pure taco2 training without vocoder -thorsten-taco2-v0.0.2 | to do | to do | to do +thorsten-taco2-ddc-v0.1 | to do | to do | to do # Feel free to file an issue if you ... * have improvements on dataset diff --git a/models/thorsten-taco2-v0.0.1/Dockerfile b/models/thorsten-taco2-v0.0.1/Dockerfile deleted file mode 100644 index 4a6e689..0000000 --- a/models/thorsten-taco2-v0.0.1/Dockerfile +++ /dev/null @@ -1,68 +0,0 @@ -# Adapted from @thorstenMueller's training script (https://github.com/thorstenMueller/TTS_recipes) -# Docker file by @repodiac (https://github.com/repodiac/tit-for-tat/thorsten-tts) -# *** Use without warranty and at your own risk! *** - -# Installation folder **inside** Docker container -# (NOTE: if it is changed to another folder, you have to manually change it to the same folder in the last line, ENTRYPOINT ...) -ARG BASEDIR=/tmp/tts - -FROM pytorch/pytorch:1.6.0-cuda10.1-cudnn7-devel as ttts-base -ARG BASEDIR -WORKDIR $BASEDIR - -# Install system libraries etc. -FROM ttts-base as ttts1 -ARG BASEDIR -WORKDIR $BASEDIR - -RUN apt-get update -RUN apt-get install -y --no-install-recommends build-essential gcc espeak-ng espeak-ng-data git git-extras -RUN pip install pip --upgrade -RUN pip install gdown - -# Clone deep-learning-german-tts repo and copy config and test sentences -RUN git clone --single-branch --branch dev https://github.com/thorstenMueller/deep-learning-german-tts.git -RUN cp $BASEDIR/deep-learning-german-tts/models/thorsten-taco2-v0.0.1/de-test-sentences.txt $BASEDIR -RUN cp $BASEDIR/deep-learning-german-tts/models/thorsten-taco2-v0.0.1/config.json $BASEDIR - -# Download and extract "thorsten-TTS" dataset -FROM ttts1 as ttts2 -ARG BASEDIR -WORKDIR $BASEDIR - -RUN cd $BASEDIR -RUN gdown https://drive.google.com/uc?id=1yKJM1LAOQpRVojKunD9r8WN_p5KzBxjc -O thorsten-dataset.tgz -RUN tar -xvzf thorsten-dataset.tgz - -# Prepare shuffled training and validate data (90% train, 10% val) -RUN shuf LJSpeech-1.1/metadata.csv > LJSpeech-1.1/metadata_shuf.csv -RUN head -n 20400 LJSpeech-1.1/metadata_shuf.csv > LJSpeech-1.1/metadata_train.csv -RUN tail -n 2268 LJSpeech-1.1/metadata_shuf.csv > LJSpeech-1.1/metadata_val.csv - -# Install Mozilla TTS repo and dependencies -FROM ttts2 as ttts3 -ARG BASEDIR -WORKDIR $BASEDIR - -RUN git clone --single-branch --branch dev https://github.com/mozilla/TTS $BASEDIR/TTS - -WORKDIR $BASEDIR/TTS -RUN python setup.py develop - -# Add german phoneme cleaner library by @repodiac -FROM ttts3 as ttts4 -ARG BASEDIR - -RUN git clone https://github.com/repodiac/german_transliterate $BASEDIR/german_transliterate -WORKDIR $BASEDIR/german_transliterate -RUN pip install -e . - -WORKDIR $BASEDIR/TTS/mozilla_voice_tts/tts/utils/text -RUN sed '/import re/a from german_transliterate.core import GermanTransliterate' cleaners.py >> cleaners-new.py -RUN mv cleaners-new.py cleaners.py -RUN echo "\ndef german_phoneme_cleaners(text):" >> cleaners.py -RUN echo "\treturn GermanTransliterate(replace={';': ',', ':': ' '}, sep_abbreviation=' -- ').transliterate(text)" >> cleaners.py - -# Run training -WORKDIR $BASEDIR/TTS/mozilla_voice_tts/bin/ -ENTRYPOINT CUDA_VISIBLE_DEVICES="0" python train_tts.py --config_path $BASEDIR/config.json diff --git a/models/thorsten-taco2-v0.0.1/README.md b/models/thorsten-taco2-v0.0.1/README.md deleted file mode 100644 index 5dd3d20..0000000 --- a/models/thorsten-taco2-v0.0.1/README.md +++ /dev/null @@ -1,3 +0,0 @@ -NOCH MIT REPODIAC KLÄREN WAS IN MEIN UND IN SEIN REPO KOMMT ODER WAS EINFACH VERLINKT WIRD - -> https://github.com/repodiac/tit-for-tat/tree/master/thorsten-TTS \ No newline at end of file diff --git a/models/thorsten-taco2-v0.0.1/config.json b/models/thorsten-taco2-v0.0.1/config.json deleted file mode 100644 index 09942b3..0000000 --- a/models/thorsten-taco2-v0.0.1/config.json +++ /dev/null @@ -1,148 +0,0 @@ -{ - "github_branch":"* master", - "restore_path":"", - "model": "Tacotron2", // one of the model in models/ - "run_name": "thorsten-v1.0.0", - "run_description": "thorsten-de v0.0.1", - - // AUDIO PARAMETERS - "audio":{ - // New "dev" branch params - "fft_size": 1024, - "spec_gain": 1.0, - - // Audio processing parameters - "num_mels": 80, // size of the mel spec frame. - "num_freq": 1025, // number of stft frequency levels. Size of the linear spectogram frame. - "sample_rate": 22050, // DATASET-RELATED: wav sample-rate. If different than the original data, it is resampled. - "win_length": 1024, // stft window length in ms. - "hop_length": 256, // stft window hop-lengh in ms. - "frame_length_ms": null, // stft window length in ms.If null, 'win_length' is used. - "frame_shift_ms": null, // stft window hop-lengh in ms. If null, 'hop_length' is used. - "preemphasis": 0.0, //0.98, // pre-emphasis to reduce spec noise and make it more structured. If 0.0, no -pre-emphasis. - "min_level_db": -100, // normalization range - "ref_level_db": 20, // reference level db, theoretically 20db is the sound of air. - "power": 1.5, // value to sharpen wav signals after GL algorithm. - "griffin_lim_iters": 60,// #griffin-lim iterations. 30-60 is a good range. Larger the value, slower the generation. - // Normalization parameters - "signal_norm": true, // normalize the spec values in range [0, 1] - "symmetric_norm": true, // move normalization to range [-1, 1] - "max_norm": 4.0, // scale normalization to range [-max_norm, max_norm] or [0, max_norm] - "clip_norm": true, // clip normalized values into the range. - "mel_fmin": 75.0, // minimum freq level for mel-spec. ~50 for male and ~95 for female voices. Tune for dataset!! - "mel_fmax": 7750.0, // maximum freq level for mel-spec. Tune for dataset!! - "do_trim_silence": true, // enable trimming of slience of audio as you load it. LJspeech (false), TWEB (false), Nancy (true) - "trim_db": 60 // threshold for timming silence. Set this according to your dataset. - }, - - // VOCABULARY PARAMETERS - // if custom character set is not defined, - // default set in symbols.py is used - "characters":{ - "pad": "_", - "eos": "~", - "bos": "^", - "characters": "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!'(),-.:;? äöüÄÖÜß", - "punctuations":"!'(),-.:;? ", - "phonemes":"iyɨʉɯuɪʏʊeøɘəɵɤoɛœɜɞʌɔæɐaɶɑɒᵻʘɓǀɗǃʄǂɠǁʛpbtdʈɖcɟkɡqɢʔɴŋɲɳnɱmʙrʀⱱɾɽɸβfvθðszʃʒʂʐçʝxɣχʁħʕhɦɬɮʋɹɻjɰlɭʎʟˈˌːˑʍwɥʜʢʡɕʑɺɧɚ˞ɫ" - }, - - // DISTRIBUTED TRAINING - "distributed":{ - "backend": "nccl", - "url": "tcp:\/\/localhost:54321" - }, - - "reinit_layers": [], // give a list of layer names to restore from the given checkpoint. If not defined, it reloads all heuristically matching layers. - - // TRAINING - "batch_size": 32, // Batch size for training. Lower values than 32 might cause hard to learn attention. It is overwritten by 'gradual_training'. - "eval_batch_size":16, - "r": 7, // Number of decoder frames to predict per iteration. Set the initial values if gradual training is enabled. - "gradual_training": [[0, 7, 64], [1, 5, 64], [50000, 3, 32], [100000, 2, 32], [200000, 1, 32]], //set gradual training steps [first_step, r, batch_size]. If it is null, gradual training is disabled. For Tacotron, you might need to reduce the 'batch_size' as you proceeed. - "loss_masking": true, // enable / disable loss masking against the sequence padding. - "ga_alpha": 10.0, // weight for guided attention loss. If > 0, guided attention is enabled. - "apex_amp_level": null, - - // VALIDATION - "run_eval": true, - "test_delay_epochs": 10, //Until attention is aligned, testing only wastes computation time. - "test_sentences_file": "/tmp/tts/de-test-sentences.txt", // set a file to load sentences to be used for testing. If it is null then we use default english sentences. - - // OPTIMIZER - "noam_schedule": false, // use noam warmup and lr schedule. - "grad_clip": 1.0, // upper limit for gradients for clipping. - "epochs": 1000, // total number of epochs to train. - "lr": 0.0005, // Initial learning rate. If Noam decay is active, maximum learning rate. - "wd": 0.000001, // Weight decay weight. - "warmup_steps": 4000, // Noam decay steps to increase the learning rate from 0 to "lr" - "seq_len_norm": false, // Normalize eash sample loss with its length to alleviate imbalanced datasets. Use it if your dataset is small or has skewed distribution of sequence lengths. - - // TACOTRON PRENET - "memory_size": -1, // ONLY TACOTRON - size of the memory queue used fro storing last decoder predictions for auto-regression. If < 0, memory queue is disabled and decoder only uses the last prediction frame. - "prenet_type": "original", // "original" or "bn". - "prenet_dropout": true, // enable/disable dropout at prenet. - - // ATTENTION - "attention_type": "original", // 'original' or 'graves' - "attention_heads": 4, // number of attention heads (only for 'graves') - "attention_norm": "softmax", // softmax or sigmoid. Suggested to use softmax for Tacotron2 and sigmoid for Tacotron. - "windowing": false, // Enables attention windowing. Used only in eval mode. - "use_forward_attn": true, // if it uses forward attention. In general, it aligns faster. - "forward_attn_mask": false, // Additional masking forcing monotonicity only in eval mode. - "transition_agent": false, // enable/disable transition agent of forward attention. - "location_attn": true, // enable_disable location sensitive attention. It is enabled for TACOTRON by default. - "bidirectional_decoder": false, // use https://arxiv.org/abs/1907.09006. Use it, if attention does not work well with your dataset. - - "double_decoder_consistency": true, - "ddc_r": 7, - - - - // STOPNET - "stopnet": true, // Train stopnet predicting the end of synthesis. - "separate_stopnet": true, // Train stopnet seperately if 'stopnet==true'. It prevents stopnet loss to influence the rest of the model. It causes a better model, but it trains SLOWER. - - // TENSORBOARD and LOGGING - "print_step": 25, // Number of steps to log traning on console. - "tb_plot_step": 100, - "print_eval": false, // If True, it prints intermediate loss values in evalulation. - "save_step": 5000, // Number of training steps expected to save traninpg stats and checkpoints. - "checkpoint": true, // If true, it saves checkpoints per "save_step" - "tb_model_param_stats": false, // true, plots param stats per layer on tensorboard. Might be memory consuming, but good for debugging. - - // DATA LOADING - //"text_cleaner": "phoneme_cleaners", - "text_cleaner": "german_phoneme_cleaners", - "enable_eos_bos_chars": false, // enable/disable beginning of sentence and end of sentence chars. - "num_loader_workers": 8, // number of training data loader processes. Don't set it too big. 4-8 are good values. - "num_val_loader_workers": 4, // number of evaluation data loader processes. - "batch_group_size": 0, //Number of batches to shuffle after bucketing. - "min_seq_len": 3, // DATASET-RELATED: minimum text length to use in training - "max_seq_len": 180, // DATASET-RELATED: maximum text length - - // PATHS - "output_path": "/tmp/tts/models/thorsten/", - - // PHONEMES - "phoneme_cache_path": "mozilla_de_phonemes", // phoneme computation is slow, therefore, it caches results in the given folder. - "use_phonemes": true, // use phonemes instead of raw characters. It is suggested for better pronounciation. - "phoneme_language": "de", // depending on your target language, pick one from https://github.com/bootphon/phonemizer#languages - - // MULTI-SPEAKER and GST - "use_speaker_embedding": false, // use speaker embedding to enable multi-speaker learning. - "style_wav_for_test": null, // path to style wav file to be used in TacotronGST inference. - "use_gst": false, // TACOTRON ONLY: use global style tokens - - // DATASETS - "datasets": // List of datasets. They all merged and they get different speaker_ids. - [ - { - "name": "ljspeech", - "path": "/tmp/tts/LJSpeech-1.1", - "meta_file_train": "metadata_train.csv", - "meta_file_val": "metadata_val.csv" - } - ] - - } \ No newline at end of file diff --git a/models/thorsten-taco2-v0.0.1/de-test-sentences.txt b/models/thorsten-taco2-v0.0.1/de-test-sentences.txt deleted file mode 100644 index ff05e7b..0000000 --- a/models/thorsten-taco2-v0.0.1/de-test-sentences.txt +++ /dev/null @@ -1,7 +0,0 @@ -Die aktuelle Außentemperatur beträgt sieben Grad Celsius und die Regenwahrscheinlichkeit liegt bei zwölf Prozent. -Die aktuelle Außentemperatur beträgt 7°C und die Regenwahrscheinlichkeit liegt bei 12%. -Frankfurt am Main wird auch Mainhattan genannt. -Ich bedanke mich bei euch für euren Support und eure Gedult bei der Erzeugung einer künstlichen Stimme. -Hallo, wie geht es Dir? -Was ist los! -Die wachsende Furcht vor den Folgen des grassierenden Coronavirus für die Weltwirtschaft hat den Dax am Dienstag auf das tiefste Niveau seit Oktober vergangenen Jahres gedrückt. \ No newline at end of file