media, wiki-publish, caption updates

* common-playbook.yml: Start moving publishing setup to res
* group_vars/all.yml: New common variables.
* inventory.yml (prod): Number of threads, new hosts
* roles/caption/templates/process-captions.py: Add mp4, try to figure
out why script was failing, simplify
* roles/media/tasks/main.yml: New role for setting up
media.emacsconf.org for this year
* roles/prerec/templates/reencode.sh: Keep a copy of zaeph's script
* roles/stream/defaults/main.yml: Add more variables
* roles/stream: Restreaming lowres
* roles/wiki-publish/tasks/emacs.yml: Build Emacs from source

1 files changed, 33 insertions, 51 deletions

diff --git a/roles/caption/templates/process-captions.py b/roles/caption/templates/process-captions.py
index 72e9ad2..66f39dd 100755
--- a/roles/caption/templates/process-captions.py
+++ b/roles/caption/templates/process-captions.py
@@ -32,16 +32,12 @@ import datetime
 import sys
 import webvtt
 import xml.etree.ElementTree as ET
-from lhotse import RecordingSet, Recording, AudioSource, SupervisionSegment, SupervisionSet, create_cut_set_eager, align_with_torchaudio, CutSet, annotate_with_whisper
-from tqdm import tqdm
-import whisper
-import re
-import os
+from lhotse import RecordinRecording, AudioSource, SupervisionSegment, SupervisionSet, create_cut_set_e
 import json
 import torch
 
-THREADS = 12
-VIDEO_REGEXP = '\.(webm|mov)$'
+THREADS = {{ cpus }}
+VIDEO_REGEXP = '\.(webm|mov|mp4)$'
 AUDIO_REGEXP = '\.(ogg|opus)$'
 ALWAYS = False
 TRIM_AUDIO = False
@@ -49,6 +45,8 @@ MODEL = os.environ.get('MODEL', 'large')  # Set to tiny for testing
 WORK_DIR = "{{ emacsconf_caption_dir }}"
 JSON_FILE = os.path.join(WORK_DIR, 'talks.json')
 
+# ----------------------------------------------------------------
+
 def get_slug_from_filename(filename):
     m = re.search('emacsconf-[0-9]+-([a-z]+)--', filename)
     if m:
@@ -155,41 +153,23 @@ def generate_srv2(work):
         captions.append(SupervisionSegment(id=rec_id + '-sup' + '%05d' % i, channel=recs[0].channel_ids[0], recording_id=rec_id, start=to_sec(caption.start), duration=to_sec(caption.end) - to_sec(caption.start), text=caption.text, language='English'))
     sups = SupervisionSet.from_segments(captions)
     main = CutSet.from_manifests(recordings=recs, supervisions=sups)
-    work['cuts'] = main.trim_to_supervisions(keep_overlapping=False,keep_all_channels=True)
+    work['cuts'] = main.trim_to_supervisions(keep_all_channels=True)
     cuts_aligned = align_with_torchaudio(work['cuts'])
     root = ET.Element("timedtext")
     doc = ET.SubElement(root, "window")
     for line, aligned in enumerate(cuts_aligned):
-        # Numbers are weird 
-        words = re.split(' ', captions[line].text)
-        tokenized_words = [re.sub('[^\'A-Z0-9]', '', w.upper()) for w in words]
-        if len(aligned.supervisions) == 0:
-            print(captions[line], aligned)
-            continue
-        aligned_words = list(aligned.supervisions[0].alignment['word'])
-        aligned_index = 0
-        aligned_len = len(aligned_words)
-        word_index = 0
-        word_len = len(words)
-        while word_index < word_len and aligned_index < aligned_len:
-            # log("Choosing %s %s" % (words[word_index], aligned_words[aligned_index].symbol))
-            ET.SubElement(doc, 'text',
-                              t=str(float(aligned_words[aligned_index].start)*1000),
-                              d=str(float(aligned_words[aligned_index].duration)*1000),
-                              w="1",
-                              append="1").text = words[word_index]
-            if tokenized_words[word_index] != aligned_words[aligned_index].symbol and word_index < word_len - 1:
-                # Scan ahead for a word that maches the next word, but don't go too far
-                cur_aligned = aligned_index
-                while aligned_index < aligned_len and aligned_index < cur_aligned + 5 and aligned_words[aligned_index].symbol != tokenized_words[word_index + 1]:
-                    log("Sliding to match %s %d %s" % (tokenized_words[word_index + 1], aligned_index, aligned_words[aligned_index].symbol))
-                    aligned_index = aligned_index + 1
-                if not aligned_words[aligned_index].symbol == tokenized_words[word_index + 1]:
-                    log("Resetting, couldn't find")
-                    aligned_index = cur_aligned + 1
-            else:
-                aligned_index = aligned_index + 1
-            word_index = word_index + 1
+        if len(aligned.supervisions) > 0:
+            aligned_words = aligned.supervisions[0].alignment['word']
+            for w, word in enumerate(aligned_words):
+                el = ET.SubElement(doc, 'text',
+                                  t=str(float(word.start)*1000),
+                                  d=str(float(word.duration)*1000),
+                                  w="1",
+                                  append="1")
+                el.text = word.symbol
+                el.tail = "\n"
+        else:
+            print("No supervisions", aligned)
     tree = ET.ElementTree(root)
     work['srv2'] = work['base'] + '.srv2'
     with open(work['srv2'], "w") as f:
@@ -218,18 +198,20 @@ directory = sys.argv[1] if len(sys.argv) > 1 else WORK_DIR
 
 needs_work = get_files_to_work_on(directory)
 if len(needs_work) > 0:
-    if THREADS > 0:
-        torch.set_num_threads(THREADS)
-    for work in needs_work:
-        log("Started processing %s" % work['base'])
-        if work['audio']:
-            if ALWAYS or not 'vtt' in work:
-                work = generate_captions(work)
-            if ALWAYS or not 'srv2' in work:
-                work = generate_srv2(work)
-    #     print("Aligning words", audio_file, datetime.datetime.now())
-    #     word_cuts = align_words(cuts)
-    #     convert_cuts_to_word_timing(audio_file, word_cuts)
-        log("Done %s" % str(work['base']))
+    while len(needs_work) > 0:
+        if THREADS > 0:
+            torch.set_num_threads(THREADS)
+            for work in needs_work:
+                log("Started processing %s" % work['base'])
+                if work['audio']:
+                    if ALWAYS or not 'vtt' in work:
+                        work = generate_captions(work)
+                    if ALWAYS or not 'srv2' in work:
+                        work = generate_srv2(work)
+                        #     print("Aligning words", audio_file, datetime.datetime.now())
+                        #     word_cuts = align_words(cuts)
+                        #     convert_cuts_to_word_timing(audio_file, word_cuts)
+                    log("Done %s" % str(work['base']))
+            needs_work = get_files_to_work_on(directory)
 else:
     log("No work needed.")