config, benchmark notebook, synthesis fixed

2026-10-24 12:00:20 +08:00 · 2019-06-26 13:31:16 +02:00
1 parent d172a3d3d5
commit 05ff8801d1
@@ -75,6 +75,7 @@
    "phoneme_cache_path": "mozilla_us_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": "en-us",     // depending on your target language, pick one from  https://github.com/bootphon/phonemizer#languages
-    "text_cleaner": "phoneme_cleaners"
+    "text_cleaner": "phoneme_cleaners",
+    "num_speakers": 10 // should just be bigger than the actual number of speakers
 }

@@ -76,6 +76,7 @@
        "phoneme_cache_path": "mozilla_us_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": "en-us",     // depending on your target language, pick one from  https://github.com/bootphon/phonemizer#languages
-        "text_cleaner": "phoneme_cleaners"
+        "text_cleaner": "phoneme_cleaners",
+        "num_speakers": 10 // should just be bigger than the actual number of speakers
    }
    
@@ -78,6 +78,7 @@
        "phoneme_cache_path": "mozilla_us_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": "en-us",     // depending on your target language, pick one from  https://github.com/bootphon/phonemizer#languages
-        "text_cleaner": "phoneme_cleaners"
+        "text_cleaner": "phoneme_cleaners",
+        "num_speakers": 10 // should just be bigger than the actual number of speakers
    }
    
@@ -76,6 +76,7 @@
                "phoneme_cache_path": "phoneme_cache",  // phoneme computation is slow, therefore, it caches results in the given folder.
                "use_phonemes": false,           // 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
-                "text_cleaner": "phoneme_cleaners"
+                "text_cleaner": "phoneme_cleaners",
+                "num_speakers": 10 // should just be bigger than the actual number of speakers
            }
            
@@ -76,6 +76,7 @@
        "phoneme_cache_path": "mozilla_us_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": "en-us",     // depending on your target language, pick one from  https://github.com/bootphon/phonemizer#languages
-        "text_cleaner": "phoneme_cleaners"
+        "text_cleaner": "phoneme_cleaners",
+        "num_speakers": 10 // should just be bigger than the actual number of speakers
    }
    
@@ -19,8 +19,10 @@
  },
  {
   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "TTS_PATH = \"/home/erogol/projects/\"\n",
@@ -29,11 +31,30 @@
  },
  {
   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n",
+      "Populating the interactive namespace from numpy and matplotlib\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/thomas/miniconda2/envs/mztts/lib/python3.6/site-packages/IPython/core/magics/pylab.py:160: UserWarning: pylab import has clobbered these variables: ['plt']\n",
+      "`%matplotlib` prevents importing * from pylab and numpy\n",
+      "  \"\\n`%matplotlib` prevents importing * from pylab and numpy\"\n"
+     ]
+    }
+   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
@@ -75,13 +96,15 @@
  },
  {
   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "def tts(model, text, speaker_id, CONFIG, use_cuda, ap, use_gl, figures=True):\n",
    "    t_1 = time.time()\n",
-    "    waveform, alignment, mel_spec, mel_postnet_spec, stop_tokens = synthesis(model, text, speaker_id, CONFIG, use_cuda, ap, False, CONFIG.enable_eos_bos_chars)\n",
+    "    waveform, alignment, mel_spec, mel_postnet_spec, stop_tokens = synthesis(model, text, speaker_id, CONFIG, use_cuda, ap, truncated=False, enable_eos_bos_chars=CONFIG.enable_eos_bos_chars)\n",
    "    if CONFIG.model == \"Tacotron\" and not use_gl:\n",
    "        mel_postnet_spec = ap.out_linear_to_mel(mel_postnet_spec.T).T\n",
    "    if not use_gl:\n",
@@ -100,15 +123,17 @@
  },
  {
   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "# Set constants\n",
    "ROOT_PATH = '/media/erogol/data_ssd/Data/models/mozilla_models/4845/'\n",
-    "MODEL_PATH = ROOT_PATH + '/best_model.pth.tar'\n",
+    "MODEL_PATH = ROOT_PATH + 'best_model.pth.tar'\n",
    "CONFIG_PATH = ROOT_PATH + '/config.json'\n",
-    "OUT_FOLDER = '/home/erogol/Dropbox/AudioSamples/benchmark_samples/'\n",
+    "OUT_FOLDER = \"/home/erogol/Dropbox/AudioSamples/benchmark_samples/\"\n",
    "CONFIG = load_config(CONFIG_PATH)\n",
    "VOCODER_MODEL_PATH = \"/media/erogol/data_ssd/Data/models/wavernn/mozilla/mozilla-May24-4763/model_checkpoints/best_model.pth.tar\"\n",
    "VOCODER_CONFIG_PATH = \"/media/erogol/data_ssd/Data/models/wavernn/mozilla/mozilla-May24-4763/config.json\"\n",
@@ -128,9 +153,39 @@
  },
  {
   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " > Using model: TacotronGST\n",
+      " > Setting up Audio Processor...\n",
+      " | > sample_rate:16000\n",
+      " | > num_mels:80\n",
+      " | > min_level_db:-100\n",
+      " | > frame_shift_ms:12.5\n",
+      " | > frame_length_ms:50\n",
+      " | > ref_level_db:20\n",
+      " | > num_freq:1025\n",
+      " | > power:1.5\n",
+      " | > preemphasis:0.98\n",
+      " | > griffin_lim_iters:60\n",
+      " | > signal_norm:True\n",
+      " | > symmetric_norm:False\n",
+      " | > mel_fmin:0.0\n",
+      " | > mel_fmax:8000.0\n",
+      " | > max_norm:1.0\n",
+      " | > clip_norm:True\n",
+      " | > do_trim_silence:False\n",
+      " | > n_fft:2048\n",
+      " | > hop_length:200\n",
+      " | > win_length:800\n",
+      "5000\n"
+     ]
+    }
+   ],
   "source": [
    "# LOAD TTS MODEL\n",
    "from utils.text.symbols import symbols, phonemes\n",
@@ -159,8 +214,10 @@
  },
  {
   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "# LOAD WAVERNN\n",
@@ -200,11 +257,65 @@
  },
  {
   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/thomas/miniconda2/envs/mztts/lib/python3.6/site-packages/librosa/util/utils.py:1725: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
+      "  if np.issubdtype(x.dtype, float) or np.issubdtype(x.dtype, complex):\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " >  Run-time: 2.2084879875183105\n",
+      "bɪl ɡoːt ɪn ðə habɪt oːf askɪŋ hɪmzɛlf iːs tɑːt (en)θɔːt(de) tɾuːə?  ant iːf heː vasnt apzoːluːtɛliː kɛɾtaɪn iːt vas, heː jʊst leːt iːt ɡoː.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/thomas/miniconda2/envs/mztts/lib/python3.6/site-packages/librosa/display.py:656: FutureWarning: Conversion of the second argument of issubdtype from `complex` to `np.complexfloating` is deprecated. In future, it will be treated as `np.complex128 == np.dtype(complex).type`.\n",
+      "  if np.issubdtype(data.dtype, np.complex):\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
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+     "metadata": {},
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+    },
+    {
+     "data": {
+      "image/png": "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 truncated
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x12d244eb8>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
   "source": [
    "model.eval()\n",
    "model.decoder.max_decoder_steps = 2000\n",
@@ -217,6 +328,7 @@
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
+    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
@@ -228,7 +340,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"The human voice is the most perfect instrument of all.\"\n",
@@ -238,7 +352,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"I'm sorry Dave. I'm afraid I can't do that.\"\n",
@@ -249,6 +365,7 @@
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
+    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
@@ -267,7 +384,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"Generative adversarial network or variational auto-encoder.\"\n",
@@ -277,7 +396,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"Scientists at the CERN laboratory say they have discovered a new particle.\"\n",
@@ -287,7 +408,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"Here’s a way to measure the acute emotional intelligence that has never gone out of style.\"\n",
@@ -297,7 +420,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"President Trump met with other leaders at the Group of 20 conference.\"\n",
@@ -307,7 +432,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"The buses aren't the problem, they actually provide a solution.\"\n",
@@ -324,7 +451,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"Generative adversarial network or variational auto-encoder.\"\n",
@@ -334,7 +463,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"Basilar membrane and otolaryngology are not auto-correlations.\"\n",
@@ -344,7 +475,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \" He has read the whole thing.\"\n",
@@ -354,7 +487,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"He reads books.\"\n",
@@ -365,6 +500,7 @@
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
+    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
@@ -377,6 +513,7 @@
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
+    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
@@ -388,7 +525,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"This is your internet browser Firefox.\"\n",
@@ -398,7 +537,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"The quick brown fox jumps over the lazy dog.\"\n",
@@ -408,7 +549,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"Does the quick brown fox jump over the lazy dog?\"\n",
@@ -418,7 +561,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"Eren, how are you?\"\n",
@@ -435,7 +580,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"Encouraged, he started with a minute a day.\"\n",
@@ -445,7 +592,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"His meditation consisted of “body scanning” which involved focusing his mind and energy on each section of the body from head to toe .\"\n",
@@ -455,7 +604,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"Recent research at Harvard has shown meditating for as little as 8 weeks can actually increase the grey matter in the parts of the brain responsible for emotional regulation and learning . \"\n",
@@ -465,7 +616,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "sentence = \"If he decided to watch TV he really watched it.\"\n",
@@ -476,6 +629,7 @@
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
+    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
@@ -487,7 +641,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "# for twb dataset\n",
@@ -498,7 +654,9 @@
  {
   "cell_type": "code",
   "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
   "outputs": [],
   "source": [
    "# !zip benchmark_samples/samples.zip benchmark_samples/*"
@@ -507,9 +665,9 @@
 ],
 "metadata": {
  "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3(mztts)",
   "language": "python",
-   "name": "python3"
+   "name": "mztts"
  },
  "language_info": {
   "codemirror_mode": {
@@ -521,7 +679,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.7.2"
+   "version": "3.6.8"
  }
 },
 "nbformat": 4,
@@ -35,17 +35,17 @@ def compute_style_mel(style_wav, ap, use_cuda):
        return style_mel


-def run_model(model, inputs, CONFIG, truncated, style_mel=None):
+def run_model(model, inputs, speaker_id, CONFIG, truncated, style_mel=None):
    if CONFIG.model == "TacotronGST" and style_mel is not None:
        decoder_output, postnet_output, alignments, stop_tokens = model.inference(
-            inputs, style_mel)
+            inputs, style_mel, speaker_id)
    else:
        if truncated:
            decoder_output, postnet_output, alignments, stop_tokens = model.inference_truncated(
-                inputs)
+                inputs, speaker_id)
        else:
            decoder_output, postnet_output, alignments, stop_tokens = model.inference(
-                inputs)
+                inputs, speaker_id)
    return decoder_output, postnet_output, alignments, stop_tokens


@@ -100,12 +100,13 @@ def synthesis(model,
        style_mel = compute_style_mel(style_wav, ap, use_cuda)
    # preprocess the given text
    inputs = text_to_seqvec(text, CONFIG, use_cuda)
-    speaker_id = speaker_id_var = torch.from_numpy(speaker_id).unsqueeze(0)
+    speaker_id = np.asarray(speaker_id)
+    speaker_id = torch.from_numpy(speaker_id).unsqueeze(0)
    if use_cuda:
        speaker_id.cuda()
    # synthesize voice
    decoder_output, postnet_output, alignments, stop_tokens = run_model(
-        model, inputs, CONFIG, truncated, style_mel)
+        model, inputs, speaker_id, CONFIG, truncated, style_mel)
    # convert outputs to numpy
    postnet_output, decoder_output, alignment = parse_outputs(
        postnet_output, decoder_output, alignments)