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Running
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Zero
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def regroup_words(
words: list[dict],
max_len: float = 15.0,
gap: float = 0.50,
) -> list[dict]:
"""
Returns a list of segments with keys:
'start', 'end', 'text', 'words'
"""
if not words:
return []
segs, seg_words = [], []
seg_start = words[0]["start"]
last_end = seg_start
for w in words:
over_max = (w["end"] - seg_start) > max_len
long_gap = (w["start"] - last_end) > gap
if (seg_words and (over_max or long_gap)):
segs.append({
"start": seg_start,
"end": last_end,
"segment": " ".join(x["word"] for x in seg_words),
})
seg_words = []
seg_start = w["start"]
seg_words.append(w)
last_end = w["end"]
# flush final segment
segs.append({
"start": seg_start,
"end": last_end,
"segment": " ".join(x["word"] for x in seg_words),
})
return segs
def text_to_words(text: str) -> list[dict]:
"""
Convert text format like "word[start:end] word[start:end]..." to word list.
Args:
text: String in format "It's[4.96:5.52] a[5.52:5.84] long[5.84:6.16]..."
Returns:
List of word dictionaries with keys: 'word', 'start', 'end'
"""
import re
if not text.strip():
return []
# Pattern to match word[start:end] format
pattern = r'(\S+?)\[([^:]+):([^\]]+)\]'
matches = re.findall(pattern, text)
words = []
for word, start_str, end_str in matches:
try:
start = float(start_str) if start_str != 'xxx' else 0.0
end = float(end_str) if end_str != 'xxx' else 0.0
words.append({
'word': word,
'start': start,
'end': end
})
except ValueError:
# Skip invalid entries
continue
return words
def words_to_text(words: list[dict]) -> str:
"""
Convert word list to text format "word[start:end] word[start:end]...".
Args:
words: List of word dictionaries with keys: 'word', 'start', 'end'
Returns:
String in format "It's[4.96:5.52] a[5.52:5.84] long[5.84:6.16]..."
"""
if not words:
return ""
text_parts = []
for word in words:
word_text = word.get('word', '')
start = word.get('start', 0.0)
end = word.get('end', 0.0)
# Format timestamps to max 2 decimal places
start_str = f"{start:.2f}".rstrip('0').rstrip('.')
end_str = f"{end:.2f}".rstrip('0').rstrip('.')
text_parts.append(f"{word_text}[{start_str}:{end_str}]")
return " ".join(text_parts)
def json_to_text(json_data: dict) -> str:
"""
Convert JSON lyrics data to text format for display.
Only uses the 'word' layer from the JSON structure.
Groups words into sentences/lines for better readability.
Args:
json_data: Dictionary with 'word' key containing list of word objects
Returns:
String with words grouped into lines: "word[start:end] word[start:end]...\nword[start:end]..."
"""
if not isinstance(json_data, dict) or 'word' not in json_data:
return ""
words = json_data['word']
# Group words into segments using the existing regroup_words function
segments = regroup_words(words, max_len=5, gap=0.50)
# Convert each segment to text format
segment_lines = []
for seg in segments:
# Extract words for this segment based on time range
seg_words = []
for word in words:
if seg['start'] <= word['start'] < seg['end'] or (
word['start'] <= seg['start'] < word['end']
):
seg_words.append(word)
if seg_words:
segment_text = words_to_text(seg_words)
segment_lines.append(segment_text)
return '\n\n'.join(segment_lines)
def round_to_quarter_beats(beat_position: float) -> float:
"""Round beat position to nearest quarter note for sample display."""
return round(beat_position * 4) / 4
def beats_to_seconds(beat_position: float, bpm: float) -> float:
"""Convert beat position to time in seconds."""
return (beat_position * 60.0) / bpm
def seconds_to_beats(time_seconds: float, bpm: float) -> float:
"""Convert time in seconds to beat position."""
return (time_seconds * bpm) / 60.0
def convert_text_time_to_beats(text: str, bpm: float, round_to_quarters: bool = False) -> str:
"""
Convert time-based text format to beats-based format.
Args:
text: String in format "word[start_sec:end_sec] ..."
bpm: Beats per minute for conversion
round_to_quarters: If True, round beats to quarter notes (for sample display)
Returns:
String in format "word[start_beat:end_beat] ..."
"""
if not text.strip():
return ""
words = text_to_words(text)
beat_words = []
for word in words:
start_beat = seconds_to_beats(word['start'], bpm)
end_beat = seconds_to_beats(word['end'], bpm)
# Round to quarter notes for sample display
if round_to_quarters:
start_beat = round_to_quarter_beats(start_beat)
end_beat = round_to_quarter_beats(end_beat)
# Format to reasonable precision
start_str = f"{start_beat:.2f}".rstrip('0').rstrip('.')
end_str = f"{end_beat:.2f}".rstrip('0').rstrip('.')
beat_words.append(f"{word['word']}[{start_str}:{end_str}]")
return " ".join(beat_words)
def beats_to_text_with_regrouping(text: str, bpm: float, round_to_quarters: bool = False) -> str:
"""
Convert time-based text to beats format with regrouping (like time mode).
Args:
text: String in format "word[start_sec:end_sec] ..."
bpm: Beats per minute for conversion
round_to_quarters: If True, round beats to quarter notes (for sample display)
Returns:
String with beats format grouped into lines
"""
if not text.strip():
return ""
# First convert to beats format
words = text_to_words(text)
beat_words = []
for word in words:
start_beat = seconds_to_beats(word['start'], bpm)
end_beat = seconds_to_beats(word['end'], bpm)
# Round to quarter notes for sample display
if round_to_quarters:
start_beat = round_to_quarter_beats(start_beat)
end_beat = round_to_quarter_beats(end_beat)
beat_words.append({
'word': word['word'],
'start': start_beat,
'end': end_beat
})
# Group beats into segments (using beat positions instead of seconds)
segments = regroup_words(beat_words, max_len=20, gap=2.0) # 20 beats max, 2 beat gap
# Convert each segment to text format
segment_lines = []
for seg in segments:
# Extract words for this segment based on beat range
seg_words = []
for word in beat_words:
if seg['start'] <= word['start'] < seg['end'] or (
word['start'] <= seg['start'] < word['end']
):
seg_words.append(word)
if seg_words:
segment_text = words_to_text(seg_words) # This will format as word[beat:beat]
segment_lines.append(segment_text)
return '\n\n'.join(segment_lines)
def convert_text_beats_to_time(text: str, bpm: float) -> str:
"""
Convert beats-based text format to time-based format.
Args:
text: String in format "word[start_beat:end_beat] ..."
bpm: Beats per minute for conversion
Returns:
String in format "word[start_sec:end_sec] ..."
"""
if not text.strip():
return ""
# Parse beats format (same pattern as time format)
words = text_to_words(text)
time_words = []
for word in words:
# Convert beat positions to time
start_time = beats_to_seconds(word['start'], bpm)
end_time = beats_to_seconds(word['end'], bpm)
# Format to reasonable precision
start_str = f"{start_time:.2f}".rstrip('0').rstrip('.')
end_str = f"{end_time:.2f}".rstrip('0').rstrip('.')
time_words.append(f"{word['word']}[{start_str}:{end_str}]")
return " ".join(time_words)
def convert_text_beats_to_time_with_regrouping(text: str, bpm: float) -> str:
"""
Convert beats-based text format to time-based format while preserving line structure.
Args:
text: String in format "word[start_beat:end_beat] ..." (can be multi-line)
bpm: Beats per minute for conversion
Returns:
String in format "word[start_sec:end_sec] ..." with preserved line breaks
"""
if not text.strip():
return ""
# Process each line separately to preserve segmentation
lines = text.split('\n')
converted_lines = []
for line in lines:
line = line.strip()
if not line:
# Preserve empty lines
converted_lines.append("")
continue
# Convert this line from beats to time
words = text_to_words(line)
time_words = []
for word in words:
# Convert beat positions to time
start_time = beats_to_seconds(word['start'], bpm)
end_time = beats_to_seconds(word['end'], bpm)
# Format to reasonable precision
start_str = f"{start_time:.2f}".rstrip('0').rstrip('.')
end_str = f"{end_time:.2f}".rstrip('0').rstrip('.')
time_words.append(f"{word['word']}[{start_str}:{end_str}]")
if time_words:
converted_lines.append(" ".join(time_words))
return "\n".join(converted_lines)
def text_to_json(text: str) -> dict:
"""
Convert text format to JSON structure expected by the model.
Creates the 'word' layer that the model needs.
Handles multi-line input by joining lines.
Args:
text: String in format "word[start:end] word[start:end]..." (can be multi-line)
Returns:
Dictionary with 'word' key containing list of word objects
"""
# Join multiple lines into single line for parsing
single_line_text = ' '.join(line.strip() for line in text.split('\n') if line.strip())
words = text_to_words(single_line_text)
return {"word": words}
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