diff --git a/speaker_encoder/compute_embeddings.py b/speaker_encoder/compute_embeddings.py index ff90acb7..69fbc32c 100644 --- a/speaker_encoder/compute_embeddings.py +++ b/speaker_encoder/compute_embeddings.py @@ -28,7 +28,7 @@ parser.add_argument( parser.add_argument( 'data_path', type=str, - help='Defines the data path. It overwrites config.json.') + help='Data path for wav files - directory or CSV file') parser.add_argument( 'output_path', type=str, @@ -36,14 +36,42 @@ parser.add_argument( parser.add_argument( '--use_cuda', type=bool, help='flag to set cuda.', default=False ) +parser.add_argument( + '--separator', type=str, help='Separator used in file if CSV is passed for data_path', default='|' +) args = parser.parse_args() c = load_config(args.config_path) ap = AudioProcessor(**c['audio']) -wav_files = glob.glob(args.data_path + '/**/*.wav', recursive=True) -output_files = [wav_file.replace(args.data_path, args.output_path).replace( +data_path = args.data_path +split_ext = os.path.splitext(data_path) +sep = args.separator + +if len(split_ext) > 0 and split_ext[1].lower() == '.csv': + # Parse CSV + print(f'CSV file: {data_path}') + with open(data_path) as f: + wav_path = os.path.join(os.path.dirname(data_path), 'wavs') + wav_files = [] + print(f'Separator is: {sep}') + for line in f: + components = line.split(sep) + if len(components) != 2: + print("Invalid line") + continue + wav_file = os.path.join(wav_path, components[0] + '.wav') + #print(f'wav_file: {wav_file}') + if os.path.exists(wav_file): + wav_files.append(wav_file) + print(f'Count of wavs imported: {len(wav_files)}') +else: + # Parse all wav files in data_path + wav_path = data_path + wav_files = glob.glob(data_path + '/**/*.wav', recursive=True) + +output_files = [wav_file.replace(wav_path, args.output_path).replace( '.wav', '.npy') for wav_file in wav_files] for output_file in output_files: diff --git a/speaker_encoder/notebooks/PlotUmapLibriTTS.ipynb b/speaker_encoder/notebooks/PlotUmapLibriTTS.ipynb index 4171659a..bc0a869a 100644 --- a/speaker_encoder/notebooks/PlotUmapLibriTTS.ipynb +++ b/speaker_encoder/notebooks/PlotUmapLibriTTS.ipynb @@ -1,27 +1,421 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Overview\n", + "\n", + "This notebook can be used with both a single or multi- speaker corpus and allows the interactive plotting of speaker embeddings linked to underlying audio (see instructions in the repo's speaker_embedding directory)\n", + "\n", + "Depending on the directory structure used for your corpus, you may need to adjust handling of **speaker_to_utter** and **locations**." + ] + }, { "cell_type": "code", "execution_count": 1, "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import glob\n", + "import random\n", + "import numpy as np\n", + "import torch\n", + "import umap\n", + "\n", + "from TTS.speaker_encoder.model import SpeakerEncoder\n", + "from TTS.utils.audio import AudioProcessor\n", + "from TTS.utils.generic_utils import load_config\n", + "\n", + "from bokeh.io import output_notebook, show\n", + "from bokeh.plotting import figure\n", + "from bokeh.models import HoverTool, ColumnDataSource, BoxZoomTool, ResetTool, OpenURL, TapTool\n", + "from bokeh.transform import factor_cmap, factor_mark\n", + "from bokeh.palettes import Category10" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For larger sets of speakers, you can use **Category20**, but you need to change it in the **pal** variable too\n", + "\n", + "List of Bokeh palettes here: http://docs.bokeh.org/en/1.4.0/docs/reference/palettes.html\n", + "\n", + "**NB:** if you have problems with other palettes, first see https://stackoverflow.com/questions/48333820/why-do-some-bokeh-palettes-raise-a-valueerror-when-used-in-factor-cmap" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
\n", + " \n", + " Loading BokehJS ...\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/javascript": [ + "\n", + "(function(root) {\n", + " function now() {\n", + " return new Date();\n", + " }\n", + "\n", + " var force = true;\n", + "\n", + " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", + " root._bokeh_onload_callbacks = [];\n", + " root._bokeh_is_loading = undefined;\n", + " }\n", + "\n", + " var JS_MIME_TYPE = 'application/javascript';\n", + " var HTML_MIME_TYPE = 'text/html';\n", + " var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n", + " var CLASS_NAME = 'output_bokeh rendered_html';\n", + "\n", + " /**\n", + " * Render data to the DOM node\n", + " */\n", + " function render(props, node) {\n", + " var script = document.createElement(\"script\");\n", + " node.appendChild(script);\n", + " }\n", + "\n", + " /**\n", + " * Handle when an output is cleared or removed\n", + " */\n", + " function handleClearOutput(event, handle) {\n", + " var cell = handle.cell;\n", + "\n", + " var id = cell.output_area._bokeh_element_id;\n", + " var server_id = cell.output_area._bokeh_server_id;\n", + " // Clean up Bokeh references\n", + " if (id != null && id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + "\n", + " if (server_id !== undefined) {\n", + " // Clean up Bokeh references\n", + " var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n", + " cell.notebook.kernel.execute(cmd, {\n", + " iopub: {\n", + " output: function(msg) {\n", + " var id = msg.content.text.trim();\n", + " if (id in Bokeh.index) {\n", + " Bokeh.index[id].model.document.clear();\n", + " delete Bokeh.index[id];\n", + " }\n", + " }\n", + " }\n", + " });\n", + " // Destroy server and session\n", + " var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n", + " cell.notebook.kernel.execute(cmd);\n", + " }\n", + " }\n", + "\n", + " /**\n", + " * Handle when a new output is added\n", + " */\n", + " function handleAddOutput(event, handle) {\n", + " var output_area = handle.output_area;\n", + " var output = handle.output;\n", + "\n", + " // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n", + " if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n", + " return\n", + " }\n", + "\n", + " var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n", + "\n", + " if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n", + " toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n", + " // store reference to embed id on output_area\n", + " output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n", + " }\n", + " if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n", + " var bk_div = document.createElement(\"div\");\n", + " bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n", + " var script_attrs = bk_div.children[0].attributes;\n", + " for (var i = 0; i < script_attrs.length; i++) {\n", + " toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n", + " }\n", + " // store reference to server id on output_area\n", + " output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n", + " }\n", + " }\n", + "\n", + " function register_renderer(events, OutputArea) {\n", + "\n", + " function append_mime(data, metadata, element) {\n", + " // create a DOM node to render to\n", + " var toinsert = this.create_output_subarea(\n", + " metadata,\n", + " CLASS_NAME,\n", + " EXEC_MIME_TYPE\n", + " );\n", + " this.keyboard_manager.register_events(toinsert);\n", + " // Render to node\n", + " var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n", + " render(props, toinsert[toinsert.length - 1]);\n", + " element.append(toinsert);\n", + " return toinsert\n", + " }\n", + "\n", + " /* Handle when an output is cleared or removed */\n", + " events.on('clear_output.CodeCell', handleClearOutput);\n", + " events.on('delete.Cell', handleClearOutput);\n", + "\n", + " /* Handle when a new output is added */\n", + " events.on('output_added.OutputArea', handleAddOutput);\n", + "\n", + " /**\n", + " * Register the mime type and append_mime function with output_area\n", + " */\n", + " OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n", + " /* Is output safe? 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\\n\"+\n", + " \"

\\n\"+\n", + " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", + " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", + " \"

\\n\"+\n", + " \"\\n\"+\n", + " \"\\n\"+\n", + " \"from bokeh.resources import INLINE\\n\"+\n", + " \"output_notebook(resources=INLINE)\\n\"+\n", + " \"\\n\"+\n", + " \"
\"}};\n", + "\n", + " function display_loaded() {\n", + " var el = document.getElementById(\"1001\");\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS is loading...\";\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " if (el != null) {\n", + " el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n", + " }\n", + " } else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(display_loaded, 100)\n", + " }\n", + " }\n", + "\n", + "\n", + " function run_callbacks() {\n", + " try {\n", + " root._bokeh_onload_callbacks.forEach(function(callback) {\n", + " if (callback != null)\n", + " callback();\n", + " });\n", + " } finally {\n", + " delete root._bokeh_onload_callbacks\n", + " }\n", + " console.debug(\"Bokeh: all callbacks have finished\");\n", + " }\n", + "\n", + " function load_libs(css_urls, js_urls, callback) {\n", + " if (css_urls == null) css_urls = [];\n", + " if (js_urls == null) js_urls = [];\n", + "\n", + " root._bokeh_onload_callbacks.push(callback);\n", + " if (root._bokeh_is_loading > 0) {\n", + " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", + " return null;\n", + " }\n", + " if (js_urls == null || js_urls.length === 0) {\n", + " run_callbacks();\n", + " return null;\n", + " }\n", + " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", + " root._bokeh_is_loading = css_urls.length + js_urls.length;\n", + "\n", + " function on_load() {\n", + " root._bokeh_is_loading--;\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n", + " run_callbacks()\n", + " }\n", + " }\n", + "\n", + " function on_error() {\n", + " console.error(\"failed to load \" + url);\n", + " }\n", + "\n", + " for (var i = 0; i < css_urls.length; i++) {\n", + " var url = css_urls[i];\n", + " const element = document.createElement(\"link\");\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.rel = \"stylesheet\";\n", + " element.type = \"text/css\";\n", + " element.href = url;\n", + " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " for (var i = 0; i < js_urls.length; i++) {\n", + " var url = js_urls[i];\n", + " var element = document.createElement('script');\n", + " element.onload = on_load;\n", + " element.onerror = on_error;\n", + " element.async = false;\n", + " element.src = url;\n", + " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", + " document.head.appendChild(element);\n", + " }\n", + " };var element = document.getElementById(\"1001\");\n", + " if (element == null) {\n", + " console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n", + " return false;\n", + " }\n", + "\n", + " function inject_raw_css(css) {\n", + " const element = document.createElement(\"style\");\n", + " element.appendChild(document.createTextNode(css));\n", + " document.body.appendChild(element);\n", + " }\n", + "\n", + " var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.3.4.min.js\"];\n", + " var css_urls = [];\n", + "\n", + " var inline_js = [\n", + " function(Bokeh) {\n", + " Bokeh.set_log_level(\"info\");\n", + " },\n", + " \n", + " function(Bokeh) {\n", + " \n", + " },\n", + " function(Bokeh) {} // ensure no trailing comma for IE\n", + " ];\n", + "\n", + " function run_inline_js() {\n", + " \n", + " if ((root.Bokeh !== undefined) || (force === true)) {\n", + " for (var i = 0; i < inline_js.length; i++) {\n", + " inline_js[i].call(root, root.Bokeh);\n", + " }if (force === true) {\n", + " display_loaded();\n", + " }} else if (Date.now() < root._bokeh_timeout) {\n", + " setTimeout(run_inline_js, 100);\n", + " } else if (!root._bokeh_failed_load) {\n", + " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", + " root._bokeh_failed_load = true;\n", + " } else if (force !== true) {\n", + " var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n", + " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", + " }\n", + "\n", + " }\n", + "\n", + " if (root._bokeh_is_loading === 0) {\n", + " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", + " run_inline_js();\n", + " } else {\n", + " load_libs(css_urls, js_urls, function() {\n", + " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", + " run_inline_js();\n", + " });\n", + " }\n", + "}(window));" + ], + "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1001\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };var element = document.getElementById(\"1001\");\n if (element == null) {\n console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n return false;\n }\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.3.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.3.4.min.js\"];\n var css_urls = [];\n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n \n function(Bokeh) {\n \n },\n function(Bokeh) {} // ensure no trailing comma for IE\n ];\n\n function run_inline_js() {\n \n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "output_notebook()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You should also adjust all the path constants to point at the relevant locations for you locally" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "MODEL_RUN_PATH = \"/home/neil/main/Projects/TTS3/speaker_encoder/libritts_360-half-September-28-2019_10+46AM-8565c50/\"\n", + "MODEL_PATH = MODEL_RUN_PATH + \"best_model.pth.tar\"\n", + "CONFIG_PATH = MODEL_RUN_PATH + \"config.json\"\n", + "\n", + "# My single speaker locations\n", + "#EMBED_PATH = \"/home/neil/main/Projects/TTS3/embeddings/neil14/\"\n", + "#AUDIO_PATH = \"/home/neil/data/Projects/NeilTTS/neil14/wavs/\"\n", + "\n", + "# My multi speaker locations\n", + "EMBED_PATH = \"/home/neil/main/Projects/TTS3/embeddings/libritts_360/\"\n", + "AUDIO_PATH = \"/home/neil/main/Projects/LibriTTS/LibriTTS/train-clean-360/\"" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "checkpoint_10000.pth.tar config.json\n", - "checkpoint_20000.pth.tar events.out.tfevents.1567518806.erogol-desktop\n", - "checkpoint_30000.pth.tar\n" + "best_model.pth.tar\r\n", + "config.json\r\n", + "events.out.tfevents.1569660396.erogol-desktop\r\n" ] } ], "source": [ - "!ls /media/erogol/data_ssd/Models/libri_tts/speaker_encoder/libritts_360-September-03-2019_03+53PM-dc69074/" + "!ls -1 $MODEL_RUN_PATH" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -29,7 +423,7 @@ "output_type": "stream", "text": [ " > Setting up Audio Processor...\n", - " | > sample_rate:16000\n", + " | > sample_rate:24000\n", " | > num_mels:40\n", " | > min_level_db:-100\n", " | > frame_shift_ms:12.5\n", @@ -46,61 +440,62 @@ " | > max_norm:4.0\n", " | > clip_norm:True\n", " | > do_trim_silence:False\n", + " | > sound_norm:False\n", " | > n_fft:2048\n", - " | > hop_length:200\n", - " | > win_length:800\n" + " | > hop_length:300\n", + " | > win_length:1200\n" ] } ], "source": [ - "import torch\n", - "import os\n", - "import umap\n", - "import random\n", - "import glob\n", - "import numpy as np\n", - "\n", - "from TTS.speaker_encoder.model import SpeakerEncoder\n", - "from TTS.utils.audio import AudioProcessor\n", - "from TTS.utils.generic_utils import load_config\n", - "\n", - "MODEL_PATH = \"/media/erogol/data_ssd/Models/libri_tts/speaker_encoder/libritts_360-half-September-28-2019_10+46AM-8565c50/best_model.pth.tar\"\n", - "CONFIG_PATH = \"/media/erogol/data_ssd/Models/libri_tts/speaker_encoder/libritts_360-September-03-2019_03+53PM-dc69074/config.json\"\n", - "EMBED_PATH = \"/home/erogol/Data/Libri-TTS/train-clean-360-embed_128/\"\n", "CONFIG = load_config(CONFIG_PATH)\n", "ap = AudioProcessor(**CONFIG['audio'])" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Bring in the embeddings created by **compute_embeddings.py**" + ] + }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "116500\n" + "Embeddings found: 116500\n" ] } ], "source": [ "embed_files = glob.glob(EMBED_PATH+\"/**/*.npy\", recursive=True)\n", - "print(len(embed_files))" + "print(f'Embeddings found: {len(embed_files)}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Check that we did indeed find an embedding" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'/home/erogol/Data/Libri-TTS/train-clean-360-embed_128/1025/75365/1025_75365_000002_000002.npy'" + "'/home/neil/main/Projects/TTS3/embeddings/libritts_360/7732/107520/7732_107520_000009_000003.npy'" ] }, - "execution_count": 3, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -109,16 +504,25 @@ "embed_files[0]" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Process the speakers\n", + "\n", + "Assumes count of **speaker_paths** corresponds to number of speakers (so a corpus in just one directory would be treated like a single speaker and the multiple directories of LibriTTS are treated as distinct speakers)" + ] + }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "904\n" + "Speaker count: 904\n" ] } ], @@ -131,19 +535,37 @@ " speaker_to_utter[speaker_path].append(embed_file)\n", " except:\n", " speaker_to_utter[speaker_path]=[embed_file]\n", - "print(len(speaker_paths))" + "print(f'Speaker count: {len(speaker_paths)}')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Set up the embeddings\n", + "\n", + "Adjust the number of speakers to select and the number of utterances from each speaker and they will be randomly sampled from the corpus" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "embeds = []\n", "labels = []\n", - "num_speakers = 20\n", - "num_utters = 10\n", + "locations = []\n", + "\n", + "# single speaker \n", + "#num_speakers = 1\n", + "#num_utters = 1000\n", + "\n", + "# multi speaker\n", + "num_speakers = 10\n", + "num_utters = 20\n", + "\n", + "\n", "speaker_idxs = np.random.choice(range(len(speaker_paths)), num_speakers, replace=False )\n", "\n", "for speaker_num, speaker_idx in enumerate(speaker_idxs):\n", @@ -154,69 +576,176 @@ " embed_path = speaker_to_utter[speaker_path][utter_idx]\n", " embed = np.load(embed_path)\n", " embeds.append(embed)\n", - " labels.append(speaker_num)\n", + " labels.append(str(speaker_num))\n", + " locations.append(embed_path.replace(EMBED_PATH, '').replace('.npy','.wav'))\n", "embeds = np.concatenate(embeds)" ] }, { - "cell_type": "code", - "execution_count": 6, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "from matplotlib import cm\n", - "viridis = cm.get_cmap('tab20', num_speakers)" + "Load embeddings with UMAP" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 10, "metadata": {}, + "outputs": [], + "source": [ + "model = umap.UMAP()\n", + "projection = model.fit_transform(embeds)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Interactively charting the data in Bokeh\n", + "\n", + "Set up various details for Bokeh to plot the data\n", + "\n", + "You can use the regular Bokeh [tools](http://docs.bokeh.org/en/1.4.0/docs/user_guide/tools.html?highlight=tools) to explore the data, with reset setting it back to normal\n", + "\n", + "Once you have started the local server (see cell below) you can then click on plotted points which will open a tab to play the audio for that point, enabling easy exploration of your corpus\n", + "\n", + "File location in the tooltip is given relative to **AUDIO_PATH**" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "scrolled": false + }, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/erogol/miniconda3/lib/python3.7/site-packages/sklearn/metrics/pairwise.py:258: RuntimeWarning: invalid value encountered in sqrt\n", - " return distances if squared else np.sqrt(distances, out=distances)\n", - "/home/erogol/miniconda3/lib/python3.7/site-packages/umap/spectral.py:229: UserWarning: Embedding a total of 5 separate connected components using meta-embedding (experimental)\n", - " n_components\n" - ] + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
\n" + ] + }, + "metadata": {}, + "output_type": "display_data" }, { "data": { - "image/png": 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\n", 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Application\",\"version\":\"1.3.4\"}};\n", + " var render_items = [{\"docid\":\"95a95da2-6471-485d-aafc-7fcb3a90c6fa\",\"roots\":{\"1007\":\"e515e894-9f0f-4373-b879-972fbfc359fa\"}}];\n", + " root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n", + "\n", + " }\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " } else {\n", + " var attempts = 0;\n", + " var timer = setInterval(function(root) {\n", + " if (root.Bokeh !== undefined) {\n", + " embed_document(root);\n", + " clearInterval(timer);\n", + " }\n", + " attempts++;\n", + " if (attempts > 100) {\n", + " console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n", + " clearInterval(timer);\n", + " }\n", + " }, 10, root)\n", + " }\n", + "})(window);" + ], + "application/vnd.bokehjs_exec.v0+json": "" }, "metadata": { - "needs_background": "light" + "application/vnd.bokehjs_exec.v0+json": { + "id": "1007" + } }, "output_type": "display_data" } ], "source": [ - "from matplotlib import pylab as plt\n", - "%matplotlib inline\n", + "source_wav_stems = ColumnDataSource(\n", + " data=dict(\n", + " x = projection.T[0].tolist(),\n", + " y = projection.T[1].tolist(),\n", + " desc=locations,\n", + " label=labels\n", + " )\n", + " )\n", "\n", - "model = umap.UMAP()\n", - "projection = model.fit_transform(embeds)\n", - "colors = [viridis(i) for i in labels]\n", + "hover = HoverTool(\n", + " tooltips=[\n", + " (\"file\", \"@desc\"),\n", + " (\"speaker\", \"@label\"),\n", + " ]\n", + " )\n", "\n", - "fig, ax = plt.subplots(figsize=(16, 10))\n", - "im = ax.scatter(projection[:, 0], projection[:, 1], c=colors)\n", - "plt.gca().set_aspect(\"equal\", \"datalim\")\n", - "plt.title(\"UMAP projection\")\n", - "plt.tight_layout()" + "# optionally consider adding these to the tooltips if you want additional detail\n", + "# for the coordinates: (\"(x,y)\", \"($x, $y)\"),\n", + "# for the index of the embedding / wav file: (\"index\", \"$index\"),\n", + "\n", + "factors = list(set(labels))\n", + "pal_size = max(len(factors), 3)\n", + "pal = Category10[pal_size]\n", + "\n", + "p = figure(plot_width=600, plot_height=400, tools=[hover,BoxZoomTool(), ResetTool(), TapTool()])\n", + "\n", + "\n", + "p.circle('x', 'y', source=source_wav_stems, color=factor_cmap('label', palette=pal, factors=factors),)\n", + "\n", + "url = \"http://localhost:8000/@desc\"\n", + "taptool = p.select(type=TapTool)\n", + "taptool.callback = OpenURL(url=url)\n", + "\n", + "show(p)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Local server to serve wav files from corpus\n", + "\n", + "This is required so that when you click on a data point the hyperlink associated with it will be served the file locally.\n", + "\n", + "There are other ways to serve this if you prefer and you can also run the commands manually on the command line\n", + "\n", + "The server will continue to run until stopped. To stop it simply interupt the kernel (ie square button or under Kernel menu)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/home/neil/main/Projects/LibriTTS/LibriTTS/train-clean-360\n", + "Serving HTTP on 0.0.0.0 port 8000 (http://0.0.0.0:8000/) ...\n", + "^C\n", + "\n", + "Keyboard interrupt received, exiting.\n" + ] + } + ], + "source": [ + "%cd $AUDIO_PATH\n", + "%pwd\n", + "!python -m http.server" + ] }, { "cell_type": "code",