diff --git a/_sources/recipes/TTS/ljspeech/vits.rst.txt b/_sources/recipes/TTS/ljspeech/vits.rst.txt index d08aa0f470..323d0adfc8 100644 --- a/_sources/recipes/TTS/ljspeech/vits.rst.txt +++ b/_sources/recipes/TTS/ljspeech/vits.rst.txt @@ -1,11 +1,11 @@ -VITS +VITS-LJSpeech =============== This tutorial shows you how to train an VITS model with the `LJSpeech `_ dataset. .. note:: - + TTS related recipes require packages in ``requirements-tts.txt``. .. note:: @@ -120,4 +120,4 @@ Download pretrained models If you don't want to train from scratch, you can download the pretrained models by visiting the following link: - - ``_ + - ``_ diff --git a/_sources/recipes/TTS/vctk/vits.rst.txt b/_sources/recipes/TTS/vctk/vits.rst.txt index 34024a5ea5..45ae9d9d20 100644 --- a/_sources/recipes/TTS/vctk/vits.rst.txt +++ b/_sources/recipes/TTS/vctk/vits.rst.txt @@ -1,11 +1,11 @@ -VITS +VITS-VCTK =============== This tutorial shows you how to train an VITS model with the `VCTK `_ dataset. .. note:: - + TTS related recipes require packages in ``requirements-tts.txt``. .. note:: diff --git a/index.html b/index.html index 0f14c52a18..737d51e4de 100644 --- a/index.html +++ b/index.html @@ -159,8 +159,8 @@

IcefallTTS
  • Fine-tune a pre-trained model
      diff --git a/objects.inv b/objects.inv index d36afb37cb..94b1427241 100644 Binary files a/objects.inv and b/objects.inv differ diff --git a/recipes/Finetune/index.html b/recipes/Finetune/index.html index 805144b3c5..25dce4b48a 100644 --- a/recipes/Finetune/index.html +++ b/recipes/Finetune/index.html @@ -22,7 +22,7 @@ - + @@ -122,7 +122,7 @@

      Fine-tune a pre-trained model - + diff --git a/recipes/TTS/index.html b/recipes/TTS/index.html index b06be2fbd3..b4883abc7f 100644 --- a/recipes/TTS/index.html +++ b/recipes/TTS/index.html @@ -21,7 +21,7 @@ - + @@ -58,8 +58,8 @@
    • Streaming ASR
    • RNN-LM
    • TTS
    • Fine-tune a pre-trained model
      • @@ -103,7 +103,7 @@

      TTS

      @@ -219,7 +219,7 @@

      Download pretrained models - +
      diff --git a/recipes/TTS/vctk/vits.html b/recipes/TTS/vctk/vits.html index 93879f608a..16fa5dbe3c 100644 --- a/recipes/TTS/vctk/vits.html +++ b/recipes/TTS/vctk/vits.html @@ -4,7 +4,7 @@ - VITS — icefall 0.1 documentation + VITS-VCTK — icefall 0.1 documentation @@ -22,7 +22,7 @@ - + @@ -58,8 +58,8 @@
    • Streaming ASR
    • RNN-LM
    • TTS
        -
      • VITS
        • -
      • VITS
          +
        • VITS-LJSpeech
          • +
        • VITS-VCTK
          • Data preparation
          • Build Monotonic Alignment Search
          • Training
            • @@ -98,7 +98,7 @@
          • Recipes
          • TTS
            • -
          • VITS
            • +
          • VITS-VCTK
          • Edit on GitHub
            • @@ -108,8 +108,8 @@
            -
            -

            VITS

            +
            +

            VITS-VCTK

            This tutorial shows you how to train an VITS model with the VCTK dataset.

            @@ -219,7 +219,7 @@

            Download pretrained models - +

            diff --git a/recipes/index.html b/recipes/index.html index 68799ba199..7d179499b6 100644 --- a/recipes/index.html +++ b/recipes/index.html @@ -119,8 +119,8 @@

            RecipesTTS
          • Fine-tune a pre-trained model
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"decoding"], [41, "decoding"], [42, "decoding"], [43, "decoding"], [44, "decoding"], [46, "decoding"], [47, "decoding"], [49, "decoding"], [55, "decoding"], [56, "decoding"], [57, "decoding"]], "Pre-trained model": [[2, "pre-trained-model"]], "Contributing": [[3, "contributing"]], "LODR for RNN Transducer": [[4, "lodr-for-rnn-transducer"]], "WER of LODR with different beam sizes": [[4, "id1"]], "Decoding with language models": [[5, "decoding-with-language-models"]], "LM rescoring for Transducer": [[6, "lm-rescoring-for-transducer"]], "WERs of LM rescoring with different beam sizes": [[6, "id1"]], "WERs of LM rescoring + LODR with different beam sizes": [[6, "id2"]], "LM-rescoring-based methods vs shallow-fusion-based methods (The numbers in each field is WER on test-clean, WER on test-other and decoding time on test-clean)": [[6, "id3"]], "Shallow fusion for Transducer": [[7, "shallow-fusion-for-transducer"]], "WERs and decoding time (on test-clean) of shallow fusion with different beam sizes": [[7, "id2"]], "Docker": [[8, "docker"]], "Introduction": [[9, "introduction"], [53, "introduction"]], "View available tags": [[9, "view-available-tags"]], "CUDA-enabled docker images": [[9, "cuda-enabled-docker-images"]], "CPU-only docker images": [[9, "cpu-only-docker-images"]], "Download a docker image (CUDA)": [[9, "download-a-docker-image-cuda"]], "Download a docker image (CPU)": [[9, "download-a-docker-image-cpu"]], "Run a docker image with GPU": [[9, "run-a-docker-image-with-gpu"]], "Run a docker image with CPU": [[9, "run-a-docker-image-with-cpu"]], "Run yesno within a docker container": [[9, "run-yesno-within-a-docker-container"]], "Update the code": [[9, "update-the-code"]], "Data preparation": [[9, "data-preparation"], [21, "data-preparation"], [31, "data-preparation"], [33, "data-preparation"], [36, "data-preparation"], [38, "data-preparation"], [39, "data-preparation"], [41, "data-preparation"], [42, "data-preparation"], [43, "data-preparation"], [44, "data-preparation"], [46, "data-preparation"], [47, "data-preparation"], [49, "data-preparation"], [55, "data-preparation"], [56, "data-preparation"], [57, "data-preparation"], [59, "data-preparation"], [60, "data-preparation"]], "Frequently Asked Questions (FAQs)": [[10, "frequently-asked-questions-faqs"]], "OSError: libtorch_hip.so: cannot open shared object file: no such file or directory": [[10, "oserror-libtorch-hip-so-cannot-open-shared-object-file-no-such-file-or-directory"]], "AttributeError: module \u2018distutils\u2019 has no attribute \u2018version\u2019": [[10, "attributeerror-module-distutils-has-no-attribute-version"]], "ImportError: libpython3.10.so.1.0: cannot open shared object file: No such file or directory": [[10, "importerror-libpython3-10-so-1-0-cannot-open-shared-object-file-no-such-file-or-directory"]], "For the more curious": [[11, "for-the-more-curious"], [12, "for-the-more-curious"], [13, "for-the-more-curious"], [15, "for-the-more-curious"], [16, "for-the-more-curious"]], "A quick look to the generated files": [[11, "a-quick-look-to-the-generated-files"]], "download": [[11, "download"]], "data": [[11, "data"]], "Environment setup": [[13, "environment-setup"]], "Create a virtual environment": [[13, "create-a-virtual-environment"]], "Install dependencies": [[13, "install-dependencies"]], "Install icefall": [[13, "install-icefall"]], "Icefall for dummies tutorial": [[14, "icefall-for-dummies-tutorial"]], "Model Export": [[15, "model-export"]], "Export the model parameters via model.state_dict()": [[15, "export-the-model-parameters-via-model-state-dict"]], "Export via torch.jit.script()": [[15, "export-via-torch-jit-script"]], "Export via torch.onnx.export()": [[15, "export-via-torch-onnx-export"]], "Huggingface": [[17, "huggingface"]], "Pre-trained models": [[18, "pre-trained-models"]], "Huggingface spaces": [[19, "huggingface-spaces"]], "YouTube Video": [[19, "youtube-video"], [21, "youtube-video"]], "Icefall": [[20, "icefall"]], "Contents:": [[20, null]], "Installation": [[21, "installation"]], "(0) Install CUDA toolkit and cuDNN": [[21, "install-cuda-toolkit-and-cudnn"]], "(1) Install torch and torchaudio": [[21, "install-torch-and-torchaudio"]], "(2) Install k2": [[21, "install-k2"]], "(3) Install lhotse": [[21, "install-lhotse"]], "(4) Download icefall": [[21, "download-icefall"]], "Installation example": [[21, "installation-example"]], "(1) Create a virtual environment": [[21, "create-a-virtual-environment"]], "(2) Install CUDA toolkit and cuDNN": [[21, "id1"]], "(3) Install torch and torchaudio": [[21, "id2"]], "(4) Install k2": [[21, "id3"]], "(5) Install lhotse": [[21, "id5"]], "(6) Download icefall": [[21, "id6"]], "Test Your Installation": [[21, "test-your-installation"]], "Export model.state_dict()": [[22, "export-model-state-dict"], [41, "export-model-state-dict"], [43, "export-model-state-dict"], [44, "export-model-state-dict"], [55, "export-model-state-dict"], [56, "export-model-state-dict"], [57, "export-model-state-dict"]], "When to use it": [[22, "when-to-use-it"], [28, "when-to-use-it"], [29, "when-to-use-it"]], "How to export": [[22, "how-to-export"], [28, "how-to-export"], [29, "how-to-export"]], "How to use the exported model": [[22, "how-to-use-the-exported-model"], [28, "how-to-use-the-exported-model"]], "Use the exported model to run decode.py": [[22, "use-the-exported-model-to-run-decode-py"]], "Export to ncnn": [[23, "export-to-ncnn"]], "Export ConvEmformer transducer models to ncnn": [[24, "export-convemformer-transducer-models-to-ncnn"]], "1. Download the pre-trained model": [[24, "download-the-pre-trained-model"], [25, "download-the-pre-trained-model"], [26, "download-the-pre-trained-model"]], "2. Install ncnn and pnnx": [[24, "install-ncnn-and-pnnx"], [25, "install-ncnn-and-pnnx"], [26, "install-ncnn-and-pnnx"]], "3. Export the model via torch.jit.trace()": [[24, "export-the-model-via-torch-jit-trace"], [25, "export-the-model-via-torch-jit-trace"], [26, "export-the-model-via-torch-jit-trace"]], "4. Export torchscript model via pnnx": [[24, "export-torchscript-model-via-pnnx"], [25, "export-torchscript-model-via-pnnx"], [26, "export-torchscript-model-via-pnnx"]], "5. Test the exported models in icefall": [[24, "test-the-exported-models-in-icefall"], [25, "test-the-exported-models-in-icefall"], [26, "test-the-exported-models-in-icefall"]], "6. Modify the exported encoder for sherpa-ncnn": [[24, "modify-the-exported-encoder-for-sherpa-ncnn"], [25, "modify-the-exported-encoder-for-sherpa-ncnn"], [26, "modify-the-exported-encoder-for-sherpa-ncnn"]], "7. (Optional) int8 quantization with sherpa-ncnn": [[24, "optional-int8-quantization-with-sherpa-ncnn"], [25, "optional-int8-quantization-with-sherpa-ncnn"]], "Export LSTM transducer models to ncnn": [[25, "export-lstm-transducer-models-to-ncnn"]], "Export streaming Zipformer transducer models to ncnn": [[26, "export-streaming-zipformer-transducer-models-to-ncnn"]], "Export to ONNX": [[27, "export-to-onnx"]], "sherpa-onnx": [[27, "sherpa-onnx"]], "Example": [[27, "example"]], "Download the pre-trained model": [[27, "download-the-pre-trained-model"], [33, "download-the-pre-trained-model"], [35, "download-the-pre-trained-model"], [36, "download-the-pre-trained-model"], [38, "download-the-pre-trained-model"], [42, "download-the-pre-trained-model"], [46, "download-the-pre-trained-model"], [47, "download-the-pre-trained-model"], [49, "download-the-pre-trained-model"]], "Export the model to ONNX": [[27, "export-the-model-to-onnx"]], "Decode sound files with exported ONNX models": [[27, 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Documentation": [[1, "contributing-to-documentation"]], "How to create a recipe": [[2, "how-to-create-a-recipe"]], "Data Preparation": [[2, "data-preparation"], [11, "data-preparation"], [35, "data-preparation"]], "Training": [[2, "training"], [9, "training"], [16, "training"], [21, "training"], [33, "training"], [35, "training"], [36, "training"], [38, "training"], [39, "training"], [41, "training"], [42, "training"], [43, "training"], [44, "training"], [46, "training"], [47, "training"], [49, "training"], [55, "training"], [56, "training"], [57, "training"], [59, "training"], [60, "training"]], "Decoding": [[2, "decoding"], [9, "decoding"], [12, "decoding"], [21, "decoding"], [33, "decoding"], [35, "decoding"], [36, "decoding"], [38, "decoding"], [39, "decoding"], [41, "decoding"], [42, "decoding"], [43, "decoding"], [44, "decoding"], [46, "decoding"], [47, "decoding"], [49, "decoding"], [55, "decoding"], [56, "decoding"], [57, "decoding"]], "Pre-trained model": [[2, "pre-trained-model"]], "Contributing": [[3, "contributing"]], "LODR for RNN Transducer": [[4, "lodr-for-rnn-transducer"]], "WER of LODR with different beam sizes": [[4, "id1"]], "Decoding with language models": [[5, "decoding-with-language-models"]], "LM rescoring for Transducer": [[6, "lm-rescoring-for-transducer"]], "WERs of LM rescoring with different beam sizes": [[6, "id1"]], "WERs of LM rescoring + LODR with different beam sizes": [[6, "id2"]], "LM-rescoring-based methods vs shallow-fusion-based methods (The numbers in each field is WER on test-clean, WER on test-other and decoding time on test-clean)": [[6, "id3"]], "Shallow fusion for Transducer": [[7, "shallow-fusion-for-transducer"]], "WERs and decoding time (on test-clean) of shallow fusion with different beam sizes": [[7, "id2"]], "Docker": [[8, "docker"]], "Introduction": [[9, "introduction"], [53, "introduction"]], "View available tags": [[9, "view-available-tags"]], "CUDA-enabled docker images": [[9, "cuda-enabled-docker-images"]], "CPU-only docker images": [[9, "cpu-only-docker-images"]], "Download a docker image (CUDA)": [[9, "download-a-docker-image-cuda"]], "Download a docker image (CPU)": [[9, "download-a-docker-image-cpu"]], "Run a docker image with GPU": [[9, "run-a-docker-image-with-gpu"]], "Run a docker image with CPU": [[9, "run-a-docker-image-with-cpu"]], "Run yesno within a docker container": [[9, "run-yesno-within-a-docker-container"]], "Update the code": [[9, "update-the-code"]], "Data preparation": [[9, "data-preparation"], [21, "data-preparation"], [31, "data-preparation"], [33, "data-preparation"], [36, "data-preparation"], [38, "data-preparation"], [39, "data-preparation"], [41, "data-preparation"], [42, "data-preparation"], [43, "data-preparation"], [44, "data-preparation"], [46, "data-preparation"], [47, "data-preparation"], [49, "data-preparation"], [55, "data-preparation"], [56, "data-preparation"], [57, "data-preparation"], [59, "data-preparation"], [60, "data-preparation"]], "Frequently Asked Questions (FAQs)": [[10, "frequently-asked-questions-faqs"]], "OSError: libtorch_hip.so: cannot open shared object file: no such file or directory": [[10, "oserror-libtorch-hip-so-cannot-open-shared-object-file-no-such-file-or-directory"]], "AttributeError: module \u2018distutils\u2019 has no attribute \u2018version\u2019": [[10, "attributeerror-module-distutils-has-no-attribute-version"]], "ImportError: libpython3.10.so.1.0: cannot open shared object file: No such file or directory": [[10, "importerror-libpython3-10-so-1-0-cannot-open-shared-object-file-no-such-file-or-directory"]], "For the more curious": [[11, "for-the-more-curious"], [12, "for-the-more-curious"], [13, "for-the-more-curious"], [15, "for-the-more-curious"], [16, "for-the-more-curious"]], "A quick look to the generated files": [[11, "a-quick-look-to-the-generated-files"]], "download": [[11, "download"]], "data": [[11, "data"]], "Environment setup": [[13, "environment-setup"]], "Create a virtual environment": [[13, "create-a-virtual-environment"]], "Install dependencies": [[13, "install-dependencies"]], "Install icefall": [[13, "install-icefall"]], "Icefall for dummies tutorial": [[14, "icefall-for-dummies-tutorial"]], "Model Export": [[15, "model-export"]], "Export the model parameters via model.state_dict()": [[15, "export-the-model-parameters-via-model-state-dict"]], "Export via torch.jit.script()": [[15, "export-via-torch-jit-script"]], "Export via torch.onnx.export()": [[15, "export-via-torch-onnx-export"]], "Huggingface": [[17, "huggingface"]], "Pre-trained models": [[18, "pre-trained-models"]], "Huggingface spaces": [[19, "huggingface-spaces"]], "YouTube Video": [[19, "youtube-video"], [21, "youtube-video"]], "Icefall": [[20, "icefall"]], "Contents:": [[20, null]], "Installation": [[21, "installation"]], "(0) Install CUDA toolkit and cuDNN": [[21, "install-cuda-toolkit-and-cudnn"]], "(1) Install torch and torchaudio": [[21, "install-torch-and-torchaudio"]], "(2) Install k2": [[21, "install-k2"]], "(3) Install lhotse": [[21, "install-lhotse"]], "(4) Download icefall": [[21, "download-icefall"]], "Installation example": [[21, "installation-example"]], "(1) Create a virtual environment": [[21, "create-a-virtual-environment"]], "(2) Install CUDA toolkit and cuDNN": [[21, "id1"]], "(3) Install torch and torchaudio": [[21, "id2"]], "(4) Install k2": [[21, "id3"]], "(5) Install lhotse": [[21, "id5"]], "(6) Download icefall": [[21, "id6"]], "Test Your Installation": [[21, "test-your-installation"]], "Export model.state_dict()": [[22, "export-model-state-dict"], [41, "export-model-state-dict"], [43, "export-model-state-dict"], [44, "export-model-state-dict"], [55, "export-model-state-dict"], [56, "export-model-state-dict"], [57, "export-model-state-dict"]], "When to use it": [[22, "when-to-use-it"], [28, "when-to-use-it"], [29, "when-to-use-it"]], "How to export": [[22, "how-to-export"], [28, "how-to-export"], [29, "how-to-export"]], "How to use the exported model": [[22, "how-to-use-the-exported-model"], [28, "how-to-use-the-exported-model"]], "Use the exported model to run decode.py": [[22, "use-the-exported-model-to-run-decode-py"]], "Export to ncnn": [[23, "export-to-ncnn"]], "Export ConvEmformer transducer models to ncnn": [[24, "export-convemformer-transducer-models-to-ncnn"]], "1. Download the pre-trained model": [[24, "download-the-pre-trained-model"], [25, "download-the-pre-trained-model"], [26, "download-the-pre-trained-model"]], "2. Install ncnn and pnnx": [[24, "install-ncnn-and-pnnx"], [25, "install-ncnn-and-pnnx"], [26, "install-ncnn-and-pnnx"]], "3. Export the model via torch.jit.trace()": [[24, "export-the-model-via-torch-jit-trace"], [25, "export-the-model-via-torch-jit-trace"], [26, "export-the-model-via-torch-jit-trace"]], "4. Export torchscript model via pnnx": [[24, "export-torchscript-model-via-pnnx"], [25, "export-torchscript-model-via-pnnx"], [26, "export-torchscript-model-via-pnnx"]], "5. Test the exported models in icefall": [[24, "test-the-exported-models-in-icefall"], [25, "test-the-exported-models-in-icefall"], [26, "test-the-exported-models-in-icefall"]], "6. Modify the exported encoder for sherpa-ncnn": [[24, "modify-the-exported-encoder-for-sherpa-ncnn"], [25, "modify-the-exported-encoder-for-sherpa-ncnn"], [26, "modify-the-exported-encoder-for-sherpa-ncnn"]], "7. 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