diff --git a/TTS/config/shared_configs.py b/TTS/config/shared_configs.py
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+++ b/TTS/config/shared_configs.py
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+from dataclasses import asdict, dataclass
+from typing import List, Union
+
+from coqpit import MISSING, Coqpit, check_argument
+
+
+@dataclass
+class BaseAudioConfig(Coqpit):
+    """Base config to definge audio processing parameters. It is used to initialize
+    ```TTS.utils.audio.AudioProcessor.```
+
+    Args:
+        fft_size (int):
+            Number of STFT frequency levels aka.size of the linear spectogram frame. Defaults to 1024.
+        win_length (int):
+            Each frame of audio is windowed by window of length ```win_length``` and then padded with zeros to match
+            ```fft_size```. Defaults to 256.
+        hop_length (int):
+            Number of audio samples between adjacent STFT columns. Defaults to 1024.
+        frame_shift_ms (int):
+            Set ```hop_length``` based on milliseconds and sampling rate.
+        frame_length_ms (int):
+            Set ```win_length``` based on milliseconds and sampling rate.
+        stft_pad_mode (str):
+            Padding method used in STFT. 'reflect' or 'center'.
+        sample_rate (int):
+            Audio sampling rate. Defaults to 22050.
+        resample (bool):
+            Enable / Disable resampling audio to ```sample_rate```. Defaults to ```False```.
+        preemphasis (float):
+            Preemphasis coefficient. Defaults to 0.0.
+        ref_level_db (int): 20
+            Reference Db level to rebase the audio signal and ignore the level below. 20Db is assumed the sound of air.
+            Defaults to 20.
+        do_sound_norm (bool):
+            Enable / Disable sound normalization to reconcile the volume differences among samples. Defaults to False.
+        do_trim_silence (bool):
+            Enable / Disable trimming silences at the beginning and the end of the audio clip. Defaults to ```True```.
+        trim_db (int):
+            Silence threshold used for silence trimming. Defaults to 45.
+        power (float):
+            Exponent used for expanding spectrogra levels before running Griffin Lim. It helps to reduce the
+            artifacts in the synthesized voice. Defaults to 1.5.
+        griffin_lim_iters (int):
+            Number of Griffing Lim iterations. Defaults to 60.
+        num_mels (int):
+            Number of mel-basis frames that defines the frame lengths of each mel-spectrogram frame. Defaults to 80.
+        mel_fmin (float): Min frequency level used for the mel-basis filters. ~50 for male and ~95 for female voices.
+            It needs to be adjusted for a dataset. Defaults to 0.
+        mel_fmax (float):
+            Max frequency level used for the mel-basis filters. It needs to be adjusted for a dataset.
+        spec_gain (int):
+            Gain applied when converting amplitude to DB. Defaults to 20.
+        signal_norm (bool):
+            enable/disable signal normalization. Defaults to True.
+        min_level_db (int):
+            minimum db threshold for the computed melspectrograms. Defaults to -100.
+        symmetric_norm (bool):
+            enable/disable symmetric normalization. If set True normalization is performed in the range [-k, k] else
+            [0, k], Defaults to True.
+        max_norm (float):
+            ```k``` defining the normalization range. Defaults to 4.0.
+        clip_norm (bool):
+            enable/disable clipping the our of range values in the normalized audio signal. Defaults to True.
+        stats_path (str):
+            Path to the computed stats file. Defaults to None.
+    """
+
+    # stft parameters
+    fft_size: int = 1024
+    win_length: int = 1024
+    hop_length: int = 256
+    frame_shift_ms: int = None
+    frame_length_ms: int = None
+    stft_pad_mode: str = "reflect"
+    # audio processing parameters
+    sample_rate: int = 22050
+    resample: bool = False
+    preemphasis: float = 0.0
+    ref_level_db: int = 20
+    do_sound_norm: bool = False
+    log_func = "np.log10"
+    # silence trimming
+    do_trim_silence: bool = True
+    trim_db: int = 45
+    # griffin-lim params
+    power: float = 1.5
+    griffin_lim_iters: int = 60
+    # mel-spec params
+    num_mels: int = 80
+    mel_fmin: float = 0.0
+    mel_fmax: float = None
+    spec_gain: int = 20
+    # normalization params
+    signal_norm: bool = True
+    min_level_db: int = -100
+    symmetric_norm: bool = True
+    max_norm: float = 4.0
+    clip_norm: bool = True
+    stats_path: str = None
+
+    def check_values(
+        self,
+    ):
+        """Check config fields"""
+        c = asdict(self)
+        check_argument("num_mels", c, restricted=True, min_val=10, max_val=2056)
+        check_argument("fft_size", c, restricted=True, min_val=128, max_val=4058)
+        check_argument("sample_rate", c, restricted=True, min_val=512, max_val=100000)
+        check_argument(
+            "frame_length_ms",
+            c,
+            restricted=True,
+            min_val=10,
+            max_val=1000,
+            alternative="win_length",
+        )
+        check_argument("frame_shift_ms", c, restricted=True, min_val=1, max_val=1000, alternative="hop_length")
+        check_argument("preemphasis", c, restricted=True, min_val=0, max_val=1)
+        check_argument("min_level_db", c, restricted=True, min_val=-1000, max_val=10)
+        check_argument("ref_level_db", c, restricted=True, min_val=0, max_val=1000)
+        check_argument("power", c, restricted=True, min_val=1, max_val=5)
+        check_argument("griffin_lim_iters", c, restricted=True, min_val=10, max_val=1000)
+
+        # normalization parameters
+        check_argument("signal_norm", c, restricted=True)
+        check_argument("symmetric_norm", c, restricted=True)
+        check_argument("max_norm", c, restricted=True, min_val=0.1, max_val=1000)
+        check_argument("clip_norm", c, restricted=True)
+        check_argument("mel_fmin", c, restricted=True, min_val=0.0, max_val=1000)
+        check_argument("mel_fmax", c, restricted=True, min_val=500.0, allow_none=True)
+        check_argument("spec_gain", c, restricted=True, min_val=1, max_val=100)
+        check_argument("do_trim_silence", c, restricted=True)
+        check_argument("trim_db", c, restricted=True)
+
+
+@dataclass
+class BaseDatasetConfig(Coqpit):
+    name: str = None
+    path: str = None
+    meta_file_train: str = None
+    meta_file_val: str = None
+    meta_file_attn_mask: str = None
+
+    def check_values(
+        self,
+    ):
+        """Check config fields"""
+        c = asdict(self)
+        check_argument("name", c, restricted=True)
+        check_argument("path", c, restricted=True)
+        check_argument("meta_file_train", c, restricted=True)
+        check_argument("meta_file_val", c, restricted=False)
+        check_argument("meta_file_attn_mask", c, restricted=False)
+
+
+@dataclass
+class BaseTrainingConfig(Coqpit):
+    """Base config to define the basic training parameters that are shared
+    among all the models.
+
+    Args:
+        batch_size (int):
+            Training batch size.
+        batch_group_size (int):
+            Number of batches to shuffle after bucketing.
+        eval_batch_size (int):
+            Validation batch size.
+        loss_masking (bool):
+            Enable / Disable masking padding segments of sequences.
+        mixed_precision (bool):
+            Enable / Disable mixed precision training. It reduces the VRAM use and allows larger batch sizes, however
+            it may also cause numerical unstability in some cases.
+        run_eval (bool):
+            Enable / Disable evaluation (validation) run. Defaults to True.
+        test_delay_epochs (int):
+            Number of epochs before starting to use evaluation runs. Initially, models do not generate meaningful
+            results, hence waiting for a couple of epochs might save some time.
+        print_eval (bool):
+            Enable / Disable console logging for evalutaion steps. If disabled then it only shows the final values at
+            the end of the evaluation. Default to ```False```.
+        print_step (int):
+            Number of steps required to print the next training log.
+        tb_plot_step (int):
+            Number of steps required to log training on Tensorboard.
+        tb_model_param_stats (bool):
+            Enable / Disable logging internal model stats for model diagnostic. It might be useful for model debugging.
+            Defaults to ```False```.
+        save_step (int):ipt
+            Number of steps required to save the next checkpoint.
+        checkpoint (bool):
+            Enable / Disable checkpointing.
+        keep_all_best (bool):
+            Enable / Disable keeping all the saved best models instead of overwriting the previous one. Defaults
+            to ```False```.
+        keep_after (int):
+            Number of steps to wait before saving all the best models. In use if ```keep_all_best == True```. Defaults
+            to 10000.
+        text_cleaner (str):
+            Text cleaner to be used at model training. It is set to be one of the cleaners in
+            ```TTS.tts.utils.text.cleaners```.
+        enable_eos_bos_chars (bool):
+            Enable / Disable using special characters indicating end-of-sentence and begining-of-sentence.
+        num_loader_workers (int):
+            Number of workers for training time dataloader.
+        num_val_loader_workers (int):
+            Number of workers for evaluation time dataloader.
+        min_seq_len (int):
+            Minimum sequence length to be used at training.
+        max_seq_len (int):
+            Maximum sequence length to be used at training. VRAM use at training depends on this parameter. Consider to
+            decrease it if you get OOM errors.
+        compute_f0 (bool):
+            Return F0 frames from the dataloader. Defaults to ```False```.
+        compute_input_seq_cache (bool):
+            Enable / Disable computing and caching phonemes sequences from character sequences at the begining of the
+            training. It allows faster data loading times and more precise max-min sequence prunning. Defaults
+            to ```False```.
+        output_path (str):
+            Path for training output folder. The nonexist part of the given path is created automatically.
+            All training outputs are saved there.
+        phoneme_cache_path (str):
+            Path to a folder to save the computed phoneme sequences.
+        datasets (List[BaseDatasetConfig]):
+            ist of DatasetConfig.
+
+    """
+
+    model: str = None
+    run_name: str = ""
+    run_description: str = ""
+    # training params
+    epochs: int = 10000
+    batch_size: int = MISSING
+    eval_batch_size: int = None
+    mixed_precision: bool = False
+    # eval params
+    run_eval: bool = True
+    test_delay_epochs: int = 0
+    print_eval: bool = False
+    # logging
+    print_step: int = 25
+    tb_plot_step: int = 100
+    tb_model_param_stats: bool = False
+    # checkpointing
+    save_step: int = 10000
+    checkpoint: bool = True
+    keep_all_best: bool = False
+    keep_after: int = 10000
+    # dataloading
+    num_loader_workers: int = None
+    num_val_loader_workers: int = None
+    use_noise_augment: bool = False
+    # paths
+    output_path: str = None
+    # distributed
+    distributed_backend: str = "nccl"
+    distributed_url: str = "tcp://localhost:54321"