Create parseinput.py

parseinput.py

@@ -0,0 +1,125 @@
+import re
+import xml.etree.ElementTree as ET
+from xml.sax import saxutils
+#import nltk
+
+# Chunked generation originally from https://github.com/serp-ai/bark-with-voice-clone
+def split_and_recombine_text(text, desired_length=100, max_length=150):
+    # return nltk.sent_tokenize(text)
+
+    # from https://github.com/neonbjb/tortoise-tts
+    """Split text it into chunks of a desired length trying to keep sentences intact."""
+    # normalize text, remove redundant whitespace and convert non-ascii quotes to ascii
+    text = re.sub(r"\n\n+", "\n", text)
+    text = re.sub(r"\s+", " ", text)
+    text = re.sub(r"[“”]", '"', text)
+
+    rv = []
+    in_quote = False
+    current = ""
+    split_pos = []
+    pos = -1
+    end_pos = len(text) - 1
+
+    def seek(delta):
+        nonlocal pos, in_quote, current
+        is_neg = delta < 0
+        for _ in range(abs(delta)):
+            if is_neg:
+                pos -= 1
+                current = current[:-1]
+            else:
+                pos += 1
+                current += text[pos]
+            if text[pos] == '"':
+                in_quote = not in_quote
+        return text[pos]
+
+    def peek(delta):
+        p = pos + delta
+        return text[p] if p < end_pos and p >= 0 else ""
+
+    def commit():
+        nonlocal rv, current, split_pos
+        rv.append(current)
+        current = ""
+        split_pos = []
+
+    while pos < end_pos:
+        c = seek(1)
+        # do we need to force a split?
+        if len(current) >= max_length:
+            if len(split_pos) > 0 and len(current) > (desired_length / 2):
+                # we have at least one sentence and we are over half the desired length, seek back to the last split
+                d = pos - split_pos[-1]
+                seek(-d)
+            else:
+                # no full sentences, seek back until we are not in the middle of a word and split there
+                while c not in "!?.\n " and pos > 0 and len(current) > desired_length:
+                    c = seek(-1)
+            commit()
+        # check for sentence boundaries
+        elif not in_quote and (c in "!?\n" or (c == "." and peek(1) in "\n ")):
+            # seek forward if we have consecutive boundary markers but still within the max length
+            while (
+                pos < len(text) - 1 and len(current) < max_length and peek(1) in "!?."
+            ):
+                c = seek(1)
+            split_pos.append(pos)
+            if len(current) >= desired_length:
+                commit()
+        # treat end of quote as a boundary if its followed by a space or newline
+        elif in_quote and peek(1) == '"' and peek(2) in "\n ":
+            seek(2)
+            split_pos.append(pos)
+    rv.append(current)
+
+    # clean up, remove lines with only whitespace or punctuation
+    rv = [s.strip() for s in rv]
+    rv = [s for s in rv if len(s) > 0 and not re.match(r"^[\s\.,;:!?]*$", s)]
+
+    return rv
+
+def is_ssml(value):
+    try:
+        ET.fromstring(value)
+    except ET.ParseError:
+        return False
+    return True
+
+def build_ssml(rawtext, selected_voice):
+    texts = rawtext.split("\n")
+    joinedparts = ""
+    for textpart in texts:
+        joinedparts = joinedparts + f"\n<voice name=\"{selected_voice}\">{saxutils.escape(textpart)}</voice>"
+    ssml = f"""<?xml version="1.0"?>
+<speak version="1.0" xmlns="http://www.w3.org/2001/10/synthesis"
+         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+         xsi:schemaLocation="http://www.w3.org/2001/10/synthesis
+                   http://www.w3.org/TR/speech-synthesis/synthesis.xsd"
+         xml:lang="en-US">
+         {joinedparts}
+</speak>
+    """
+    return ssml
+
+def create_clips_from_ssml(ssmlinput):
+    # Parse the XML
+    tree = ET.ElementTree(ET.fromstring(ssmlinput))
+    root = tree.getroot()
+
+    # Create an empty list
+    voice_list = []
+
+    # Loop through all voice tags
+    for voice in root.iter('{http://www.w3.org/2001/10/synthesis}voice'):
+        # Extract the voice name attribute and the content text
+        voice_name = voice.attrib['name']
+        voice_content = voice.text.strip() if voice.text else ''
+        if(len(voice_content) > 0):
+            parts = split_and_recombine_text(voice_content)
+            for p in parts:
+                # add to tuple list
+                voice_list.append((voice_name, p))
+
+    return voice_list