Upload

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text

.github/FUNDING.yml

@@ -0,0 +1,13 @@
+# These are supported funding model platforms
+
+github: [Pranjalya]
+patreon: # Replace with a single Patreon username
+open_collective: # Replace with a single Open Collective username
+ko_fi: # Replace with a single Ko-fi username
+tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel
+community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry
+liberapay: # Replace with a single Liberapay username
+issuehunt: # Replace with a single IssueHunt username
+otechie: # Replace with a single Otechie username
+lfx_crowdfunding: # Replace with a single LFX Crowdfunding project-name e.g., cloud-foundry
+custom: # Replace with up to 4 custom sponsorship URLs e.g., ['link1', 'link2']

.gitignore

@@ -0,0 +1,135 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+.idea/*
+.models/*
+.custom/*
+results/*
+debug_states/*

CITATION.cff

@@ -0,0 +1,10 @@
+cff-version: 1.3.0
+message: "If you use this software, please cite it as below."
+authors:
+- family-names: "Betker"
+  given-names: "James"
+  orcid: "https://orcid.org/my-orcid?orcid=0000-0003-3259-4862"
+title: "TorToiSe text-to-speech"
+version: 2.0
+date-released: 2022-04-28
+url: "https://github.com/neonbjb/tortoise-tts"

LICENSE

@@ -0,0 +1,201 @@
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MANIFEST.in

@@ -0,0 +1,2 @@
+recursive-include tortoise/data *
+recursive-include tortoise/voices *

app.py

@@ -0,0 +1,146 @@
+import os
+import gradio as gr
+import torchaudio
+import time
+from datetime import datetime
+from tortoise.api import TextToSpeech
+from tortoise.utils.audio import load_audio, load_voice, load_voices
+
+VOICE_OPTIONS = [
+    "random",  # special option for random voice
+    "custom_voice",  # special option for custom voice
+    "disabled",  # special option for disabled voice
+]
+
+
+def inference(text, emotion, prompt, voice, mic_audio, voice_b, voice_c, preset, seed):
+    if voice != "custom_voice":
+        voices = [voice]
+    else:
+        voices = []
+
+    if voice_b != "disabled":
+        voices.append(voice_b)
+    if voice_c != "disabled":
+        voices.append(voice_c)
+
+    if emotion != "None/Custom":
+        text = f"[I am really {emotion.lower()},] {text}"
+    elif prompt.strip() != "":
+        text = f"[{prompt},] {text}"
+
+    c = None
+    if voice == "custom_voice":
+        if mic_audio is None:
+            raise gr.Error("Please provide audio from mic when choosing custom voice")
+        c = load_audio(mic_audio, 22050)
+
+
+    if len(voices) == 1 or len(voices) == 0:
+        if voice == "custom_voice":
+            voice_samples, conditioning_latents = [c], None
+        else:
+            voice_samples, conditioning_latents = load_voice(voice)
+    else:
+        voice_samples, conditioning_latents = load_voices(voices)
+        if voice == "custom_voice":
+            voice_samples.extend([c])
+
+    sample_voice = voice_samples[0] if len(voice_samples) else None
+
+    start_time = time.time()
+    gen, _ = tts.tts_with_preset(
+        text,
+        voice_samples=voice_samples,
+        conditioning_latents=conditioning_latents,
+        preset=preset,
+        use_deterministic_seed=seed,
+        return_deterministic_state=True,
+        k=3,
+    )
+
+    with open("Tortoise_TTS_Runs.log", "a") as f:
+        f.write(
+            f"{datetime.now()} | Voice: {','.join(voices)} | Text: {text} | Quality: {preset} | Time Taken (s): {time.time()-start_time} | Seed: {seed}\n"
+        )
+
+    return (
+        (22050, sample_voice.squeeze().cpu().numpy()),
+        (24000, gen[0].squeeze().cpu().numpy()),
+        (24000, gen[1].squeeze().cpu().numpy()),
+        (24000, gen[2].squeeze().cpu().numpy()),
+    )
+
+
+def main():
+    text = gr.Textbox(lines=4, label="Text:")
+    emotion = gr.Radio(
+        ["None/Custom", "Happy", "Sad", "Angry", "Disgusted", "Arrogant"],
+        value="None/Custom",
+        label="Select emotion:",
+        type="value",
+    )
+    prompt = gr.Textbox(lines=1, label="Enter prompt if [Custom] emotion:")
+    preset = gr.Radio(
+        ["ultra_fast", "fast", "standard", "high_quality"],
+        value="fast",
+        label="Preset mode (determines quality with tradeoff over speed):",
+        type="value",
+    )
+    voice = gr.Dropdown(
+        os.listdir(os.path.join("tortoise", "voices")) + VOICE_OPTIONS,
+        value="angie",
+        label="Select voice:",
+        type="value",
+    )
+    mic_audio = gr.Audio(
+        label="Record voice (when selected custom_voice):",
+        source="microphone",
+        type="filepath",
+    )
+    voice_b = gr.Dropdown(
+        os.listdir(os.path.join("tortoise", "voices")) + VOICE_OPTIONS,
+        value="disabled",
+        label="(Optional) Select second voice:",
+        type="value",
+    )
+    voice_c = gr.Dropdown(
+        os.listdir(os.path.join("tortoise", "voices")) + VOICE_OPTIONS,
+        value="disabled",
+        label="(Optional) Select third voice:",
+        type="value",
+    )
+    seed = gr.Number(value=0, precision=0, label="Seed (for reproducibility):")
+
+    selected_voice = gr.Audio(label="Sample of selected voice (first):")
+    output_audio_1 = gr.Audio(label="Output [Candidate 1]:")
+    output_audio_2 = gr.Audio(label="Output [Candidate 2]:")
+    output_audio_3 = gr.Audio(label="Output [Candidate 3]:")
+
+    interface = gr.Interface(
+        fn=inference,
+        inputs=[
+            text,
+            emotion,
+            prompt,
+            voice,
+            mic_audio,
+            voice_b,
+            voice_c,
+            preset,
+            seed,
+        ],
+        outputs=[selected_voice, output_audio_1, output_audio_2, output_audio_3],
+    )
+    interface.launch(share=True)
+
+
+if __name__ == "__main__":
+    tts = TextToSpeech()
+
+    with open("Tortoise_TTS_Runs.log", "a") as f:
+        f.write(
+            f"\n\n-------------------------Tortoise TTS Logs, {datetime.now()}-------------------------\n"
+        )
+
+    main()

app_read.py

@@ -0,0 +1,204 @@
+import os
+import torch
+import gradio as gr
+import torchaudio
+import time
+from datetime import datetime
+from tortoise.api import TextToSpeech
+from tortoise.utils.text import split_and_recombine_text
+from tortoise.utils.audio import load_audio, load_voice, load_voices
+
+VOICE_OPTIONS = [
+    "raider_male",
+    "sebastian",
+    "jacoren",
+    "cond_latent_example",
+    "deniro",
+    "freeman",
+    "halle",
+    "lj",
+    "myself",
+    "pat2",
+    "snakes",
+    "tom",
+    "train_daws",
+    "train_dreams",
+    "train_grace",
+    "train_lescault",
+    "weaver",
+    "applejack",
+    "daniel",
+    "emma",
+    "geralt",
+    "jlaw",
+    "mol",
+    "pat",
+    "rainbow",
+    "tim_reynolds",
+    "train_atkins",
+    "train_dotrice",
+    "train_empire",
+    "train_kennard",
+    "train_mouse",
+    "william",
+    "random",  # special option for random voice
+    "custom_voice",  # special option for custom voice
+    "disabled",  # special option for disabled voice
+]
+
+
+def inference(
+    text,
+    script,
+    name,
+    voice,
+    voice_b,
+    voice_c,
+    preset,
+    seed,
+    regenerate,
+    split_by_newline,
+):
+    if regenerate.strip() == "":
+        regenerate = None
+
+    if name.strip() == "":
+        raise gr.Error("No name provided")
+
+    if text is None or text.strip() == "":
+        with open(script.name) as f:
+            text = f.read()
+        if text.strip() == "":
+            raise gr.Error("Please provide either text or script file with content.")
+
+    if split_by_newline == "Yes":
+        texts = list(filter(lambda x: x.strip() != "", text.split("\n")))
+    else:
+        texts = split_and_recombine_text(text)
+
+    os.makedirs(os.path.join("longform", name), exist_ok=True)
+
+    if regenerate is not None:
+        regenerate = list(map(int, regenerate.split()))
+
+    voices = [voice]
+    if voice_b != "disabled":
+        voices.append(voice_b)
+    if voice_c != "disabled":
+        voices.append(voice_c)
+
+    if len(voices) == 1:
+        voice_samples, conditioning_latents = load_voice(voice)
+    else:
+        voice_samples, conditioning_latents = load_voices(voices)
+
+    start_time = time.time()
+
+    all_parts = []
+    for j, text in enumerate(texts):
+        if regenerate is not None and j + 1 not in regenerate:
+            all_parts.append(
+                load_audio(os.path.join("longform", name, f"{j+1}.wav"), 24000)
+            )
+            continue
+        gen = tts.tts_with_preset(
+            text,
+            voice_samples=voice_samples,
+            conditioning_latents=conditioning_latents,
+            preset=preset,
+            k=1,
+            use_deterministic_seed=seed,
+        )
+
+        gen = gen.squeeze(0).cpu()
+        torchaudio.save(os.path.join("longform", name, f"{j+1}.wav"), gen, 24000)
+
+        all_parts.append(gen)
+
+    full_audio = torch.cat(all_parts, dim=-1)
+
+    os.makedirs("outputs", exist_ok=True)
+    torchaudio.save(os.path.join("outputs", f"{name}.wav"), full_audio, 24000)
+
+    with open("Tortoise_TTS_Runs_Scripts.log", "a") as f:
+        f.write(
+            f"{datetime.now()} | Voice: {','.join(voices)} | Text: {text} | Quality: {preset} | Time Taken (s): {time.time()-start_time} | Seed: {seed}\n"
+        )
+
+    output_texts = [f"({j+1}) {texts[j]}" for j in range(len(texts))]
+
+    return ((24000, full_audio.squeeze().cpu().numpy()), "\n".join(output_texts))
+
+
+def main():
+    text = gr.Textbox(
+        lines=4,
+        label="Text (Provide either text, or upload a newline separated text file below):",
+    )
+    script = gr.File(label="Upload a text file")
+    name = gr.Textbox(
+        lines=1, label="Name of the output file / folder to store intermediate results:"
+    )
+    preset = gr.Radio(
+        ["ultra_fast", "fast", "standard", "high_quality"],
+        value="fast",
+        label="Preset mode (determines quality with tradeoff over speed):",
+        type="value",
+    )
+    voice = gr.Dropdown(
+        VOICE_OPTIONS, value="angie", label="Select voice:", type="value"
+    )
+    voice_b = gr.Dropdown(
+        VOICE_OPTIONS,
+        value="disabled",
+        label="(Optional) Select second voice:",
+        type="value",
+    )
+    voice_c = gr.Dropdown(
+        VOICE_OPTIONS,
+        value="disabled",
+        label="(Optional) Select third voice:",
+        type="value",
+    )
+    seed = gr.Number(value=0, precision=0, label="Seed (for reproducibility):")
+    regenerate = gr.Textbox(
+        lines=1,
+        label="Comma-separated indices of clips to regenerate [starting from 1]",
+    )
+    split_by_newline = gr.Radio(
+        ["Yes", "No"],
+        label="Split by newline (If [No], it will automatically try to find relevant splits):",
+        type="value",
+        value="No",
+    )
+    output_audio = gr.Audio(label="Combined audio:")
+    output_text = gr.Textbox(label="Split texts with indices:", lines=10)
+
+    interface = gr.Interface(
+        fn=inference,
+        inputs=[
+            text,
+            script,
+            name,
+            voice,
+            voice_b,
+            voice_c,
+            preset,
+            seed,
+            regenerate,
+            split_by_newline,
+        ],
+        outputs=[output_audio, output_text],
+    )
+    interface.launch(share=False)
+
+
+if __name__ == "__main__":
+    tts = TextToSpeech()
+
+    with open("Tortoise_TTS_Runs_Scripts.log", "a") as f:
+        f.write(
+            f"\n\n-------------------------Tortoise TTS Scripts Logs, {datetime.now()}-------------------------\n"
+        )
+
+    main()

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