| import io |
| import os |
| import pickle |
| import re |
|
|
| import soundfile as sf |
| import numpy as np |
| from pydub import AudioSegment |
| from pyloudnorm import Meter |
|
|
| os.chdir(os.path.dirname(os.path.abspath(__file__))) |
|
|
| def normalize_audio_loudness(data: bytes, target_loudness: float = -23.0) -> bytes: |
| audio = AudioSegment.from_file(io.BytesIO(data), format='mp3') |
| meter = Meter(audio.frame_rate) |
| sr = audio.frame_rate |
| samples = audio.get_array_of_samples() |
| audio = np.array(samples, dtype=np.float64) |
|
|
| |
| loudness = meter.integrated_loudness(audio) |
|
|
| |
| gain_db = target_loudness - loudness |
| gain_linear = 10 ** (gain_db / 20.0) |
|
|
| |
| balanced_audio = audio * gain_linear |
|
|
| |
| balanced_audio = np.tanh(balanced_audio) |
|
|
| |
| balanced_audio = (balanced_audio * 32767).astype(np.int16) |
| byte_io = io.BytesIO() |
| sf.write(byte_io, balanced_audio, sr, format='mp3') |
| normalized_audio_bytes = byte_io.getvalue() |
|
|
| return normalized_audio_bytes |
|
|
| def get_length(text: str) -> float: |
| def calculate_string_length(text: str) -> float: |
| def split_into_words(s: str) -> list[str]: |
| return re.findall(r"\b\w+\b|[^\w\s]|\s+", s) |
|
|
| def calculate_effective_length(words: list[str]) -> float: |
| length = 0 |
| for word in words: |
| if re.match(r"^[\u4e00-\u9fff\u3040-\u30ff\u3400-\u4dbf]+$", word): |
| length += len(word) |
| elif re.match(r"^\w+$", word): |
| length += 1 |
| else: |
| length += len(word) * 0.5 |
| return length |
|
|
| words = split_into_words(text) |
| return calculate_effective_length(words) |
|
|
| return calculate_string_length(text) |
|
|
| if __name__ == "__main__": |
| normalize_audio_loudness() |
