Spaces:
Running
on
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Running
on
Zero
mrfakename
commited on
Commit
•
a9a195b
1
Parent(s):
e2646fd
Sync from GitHub repo
Browse filesThis Space is synced from the GitHub repo: https://github.com/SWivid/F5-TTS. Please submit contributions to the Space there
app.py
CHANGED
@@ -209,7 +209,8 @@ def split_text_into_batches(text, max_chars=200, split_words=SPLIT_WORDS):
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batches.append(current_batch)
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return batches
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-
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def infer_batch(ref_audio, ref_text, gen_text_batches, exp_name, remove_silence, progress=gr.Progress()):
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if exp_name == "F5-TTS":
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ema_model = F5TTS_ema_model
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@@ -294,6 +295,7 @@ def infer_batch(ref_audio, ref_text, gen_text_batches, exp_name, remove_silence,
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return (target_sample_rate, final_wave), spectrogram_path
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def infer(ref_audio_orig, ref_text, gen_text, exp_name, remove_silence, custom_split_words=''):
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if not custom_split_words.strip():
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custom_words = [word.strip() for word in custom_split_words.split(',')]
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@@ -342,7 +344,8 @@ def infer(ref_audio_orig, ref_text, gen_text, exp_name, remove_silence, custom_s
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gr.Info(f"Generating audio using {exp_name} in {len(gen_text_batches)} batches")
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return infer_batch((audio, sr), ref_text, gen_text_batches, exp_name, remove_silence)
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-
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def generate_podcast(script, speaker1_name, ref_audio1, ref_text1, speaker2_name, ref_audio2, ref_text2, exp_name, remove_silence):
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# Split the script into speaker blocks
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speaker_pattern = re.compile(f"^({re.escape(speaker1_name)}|{re.escape(speaker2_name)}):", re.MULTILINE)
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@@ -678,7 +681,7 @@ with gr.Blocks() as app_emotional:
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# Output audio
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audio_output_emotional = gr.Audio(label="Synthesized Audio")
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-
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def generate_emotional_speech(
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regular_audio,
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regular_ref_text,
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batches.append(current_batch)
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return batches
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+
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+
@gpu_decorator
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def infer_batch(ref_audio, ref_text, gen_text_batches, exp_name, remove_silence, progress=gr.Progress()):
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if exp_name == "F5-TTS":
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ema_model = F5TTS_ema_model
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return (target_sample_rate, final_wave), spectrogram_path
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+
@gpu_decorator
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def infer(ref_audio_orig, ref_text, gen_text, exp_name, remove_silence, custom_split_words=''):
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if not custom_split_words.strip():
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custom_words = [word.strip() for word in custom_split_words.split(',')]
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gr.Info(f"Generating audio using {exp_name} in {len(gen_text_batches)} batches")
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return infer_batch((audio, sr), ref_text, gen_text_batches, exp_name, remove_silence)
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+
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@gpu_decorator
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def generate_podcast(script, speaker1_name, ref_audio1, ref_text1, speaker2_name, ref_audio2, ref_text2, exp_name, remove_silence):
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# Split the script into speaker blocks
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speaker_pattern = re.compile(f"^({re.escape(speaker1_name)}|{re.escape(speaker2_name)}):", re.MULTILINE)
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# Output audio
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audio_output_emotional = gr.Audio(label="Synthesized Audio")
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@gpu_decorator
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def generate_emotional_speech(
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regular_audio,
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regular_ref_text,
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