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Multivoice

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This commit is contained in:
Chi Kim
2024-10-17 12:08:46 -04:00
parent 1a09b80482
commit cfa9382a57
6 changed files with 69 additions and 20 deletions
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69
inference-cli.py
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@@ -282,29 +282,12 @@ def infer_batch(ref_audio, ref_text, gen_text_batches, model, remove_silence, cr
final_wave = new_wave
with open(wave_path, "wb") as f:
sf.write(f.name, final_wave, target_sample_rate)
# Remove silence
if remove_silence:
aseg = AudioSegment.from_file(f.name)
non_silent_segs = silence.split_on_silence(aseg, min_silence_len=1000, silence_thresh=-50, keep_silence=500)
non_silent_wave = AudioSegment.silent(duration=0)
for non_silent_seg in non_silent_segs:
non_silent_wave += non_silent_seg
aseg = non_silent_wave
aseg.export(f.name, format="wav")
print(f.name)
# Create a combined spectrogram
combined_spectrogram = np.concatenate(spectrograms, axis=1)
save_spectrogram(combined_spectrogram, spectrogram_path)
print(spectrogram_path)
return final_wave, combined_spectrogram
def infer(ref_audio_orig, ref_text, gen_text, model, remove_silence, cross_fade_duration=0.15):
print(gen_text)
def process_voice(ref_audio_orig, ref_text):
print("Converting audio...")
with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as f:
aseg = AudioSegment.from_file(ref_audio_orig)
@@ -340,7 +323,10 @@ def infer(ref_audio_orig, ref_text, gen_text, model, remove_silence, cross_fade_
print("Finished transcription")
else:
print("Using custom reference text...")
return ref_audio, ref_text
def infer(ref_audio, ref_text, gen_text, model, remove_silence, cross_fade_duration=0.15):
print(gen_text)
# Add the functionality to ensure it ends with ". "
if not ref_text.endswith(". ") and not ref_text.endswith("。"):
if ref_text.endswith("."):
@@ -360,4 +346,47 @@ def infer(ref_audio_orig, ref_text, gen_text, model, remove_silence, cross_fade_
return infer_batch((audio, sr), ref_text, gen_text_batches, model, remove_silence, cross_fade_duration)
infer(ref_audio, ref_text, gen_text, model, remove_silence)
def process(ref_audio, ref_text, text_gen, model, remove_silence):
main_voice = {"ref_audio":ref_audio, "ref_text":ref_text}
if "voices" not in config:
voices = {"main": main_voice}
else:
voices = config["voices"]
voices["main"] = main_voice
for voice in voices:
voices[voice]['ref_audio'], voices[voice]['ref_text'] = process_voice(voices[voice]['ref_audio'], voices[voice]['ref_text'])
generated_audio_segments = []
reg1 = r'(?=\[\w+\])'
chunks = re.split(reg1, text_gen)
reg2 = r'\[(\w+)\]'
for text in chunks:
match = re.match(reg2, text)
if not match or voice not in voices:
voice = "main"
else:
voice = match[1]
text = re.sub(reg2, "", text)
gen_text = text.strip()
ref_audio = voices[voice]['ref_audio']
ref_text = voices[voice]['ref_text']
print(f"Voice: {voice}")
audio, spectragram = infer(ref_audio, ref_text, gen_text, model, remove_silence)
generated_audio_segments.append(audio)
if generated_audio_segments:
final_wave = np.concatenate(generated_audio_segments)
with open(wave_path, "wb") as f:
sf.write(f.name, final_wave, target_sample_rate)
# Remove silence
if remove_silence:
aseg = AudioSegment.from_file(f.name)
non_silent_segs = silence.split_on_silence(aseg, min_silence_len=1000, silence_thresh=-50, keep_silence=500)
non_silent_wave = AudioSegment.silent(duration=0)
for non_silent_seg in non_silent_segs:
non_silent_wave += non_silent_seg
aseg = non_silent_wave
aseg.export(f.name, format="wav")
print(f.name)
process(ref_audio, ref_text, gen_text, model, remove_silence)