From b557d32d8cb08955bdd852530921ce49145b4e8d Mon Sep 17 00:00:00 2001
From: Eren Golge <egolge@mozilla.com>
Date: Mon, 24 Jun 2019 16:58:24 +0200
Subject: [PATCH] add synthesize.py script  to call TTS on terminal

---
 synthesize.py | 147 ++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 147 insertions(+)
 create mode 100644 synthesize.py

diff --git a/synthesize.py b/synthesize.py
new file mode 100644
index 00000000..8f338636
--- /dev/null
+++ b/synthesize.py
@@ -0,0 +1,147 @@
+import os
+import time
+import argparse
+import torch
+import string
+
+from utils.synthesis import synthesis
+from utils.generic_utils import load_config, setup_model
+from utils.text.symbols import symbols, phonemes
+from utils.audio import AudioProcessor
+
+from WaveRNN.models.wavernn import Model as VocoderModel
+
+
+def tts(model,
+        vocoder_model,
+        C,
+        VC,
+        text,
+        ap,
+        use_cuda,
+        batched_vocoder,
+        figures=False):
+    t_1 = time.time()
+    use_vocoder_model = vocoder_model is not None
+    waveform, alignment, decoder_outputs, postnet_output, stop_tokens = synthesis(
+        model, text, C, use_cuda, ap, False, C.enable_eos_bos_chars)
+    if C.model == "Tacotron" and use_vocoder_model:
+        postnet_output = ap.out_linear_to_mel(postnet_output.T).T
+    if use_vocoder_model:
+        vocoder_input = torch.FloatTensor(postnet_output.T).unsqueeze(0)
+        waveform = vocoder_model.generate(
+            vocoder_input.cuda() if use_cuda else vocoder_input,
+            batched=batched_vocoder,
+            target=11000,
+            overlap=550)
+    print(" >  Run-time: {}".format(time.time() - t_1))
+    return alignment, postnet_output, stop_tokens, waveform
+
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        'text', type=str, help='Text to generate speech.')
+    parser.add_argument(
+        'config_path',
+        type=str,
+        help='Path to model config file.'
+    )
+    parser.add_argument(
+        'model_path',
+        type=str,
+        help='Path to model file.',
+    )
+    parser.add_argument(
+        'out_path',
+        type=str,
+        help='Path to save final wav file.',
+    )
+    parser.add_argument(
+        '--use_cuda', type=bool, help='Run model on CUDA.', default=False)
+    parser.add_argument(
+        '--vocoder_path',
+        type=str,
+        help=
+        'Path to vocoder model file. If it is not defined, model uses GL as vocoder. Please make sure that you installed vocoder library before (WaveRNN).',
+        default="",
+    )
+    parser.add_argument(
+        '--vocoder_config_path',
+        type=str,
+        help='Path to vocoder model config file.',
+        default="")
+    parser.add_argument(
+        '--batched_vocoder',
+        type=bool,
+        help="If True, vocoder model uses faster batch processing.",
+        default=True)
+    args = parser.parse_args()
+
+    if args.vocoder_path != "":
+        assert args.use_cuda, " [!] Enable cuda for vocoder."
+
+    # load the config
+    C = load_config(args.config_path)
+    C.forward_attn_mask = True
+
+    # load the audio processor
+    ap = AudioProcessor(**C.audio)
+
+    # load the model
+    num_chars = len(phonemes) if C.use_phonemes else len(symbols)
+    model = setup_model(num_chars, C)
+    cp = torch.load(args.model_path)
+    model.load_state_dict(cp['model'])
+    model.eval()
+    if args.use_cuda:
+        model.cuda()
+
+    # load vocoder model
+    if args.vocoder_path != "":
+        VC = load_config(args.vocoder_config_path)
+        bits = 10
+        vocoder_model = VocoderModel(
+            rnn_dims=512,
+            fc_dims=512,
+            mode=VC.mode,
+            mulaw=VC.mulaw,
+            pad=VC.pad,
+            upsample_factors=VC.upsample_factors,
+            feat_dims=VC.audio["num_mels"],
+            compute_dims=128,
+            res_out_dims=128,
+            res_blocks=10,
+            hop_length=ap.hop_length,
+            sample_rate=ap.sample_rate,
+        )
+
+        check = torch.load(args.vocoder_path)
+        vocoder_model.load_state_dict(check['model'])
+        vocoder_model.eval()
+        if args.use_cuda:
+            vocoder_model.cuda()
+    else:
+        vocoder_model = None
+        VC = None
+
+    # synthesize voice
+    print(" > Text: {}".format(args.text))
+    _, _, _, wav = tts(
+        model,
+        vocoder_model,
+        C,
+        VC,
+        args.text,
+        ap,
+        args.use_cuda,
+        args.batched_vocoder,
+        figures=False)
+
+    # save the results
+    file_name = args.text.replace(" ", "_")
+    file_name = file_name.translate(str.maketrans('', '', string.punctuation.replace('_', '')))+'.wav'
+    out_path = os.path.join(args.out_path, file_name)
+    print(" > Saving output to {}".format(out_path))
+    ap.save_wav(wav, out_path)