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--- |
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license: mit |
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task_categories: |
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- text-to-speech |
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- text-to-audio |
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language: |
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- en |
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image: |
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- https://ibb.co/ZzFkfWZ |
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tags: |
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- code |
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- music |
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pretty_name: Text-to-ASMR |
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size_categories: |
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- 1K<n<10K |
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--- |
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# End-To-End TEXT-2-ASMR with Transformers |
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This repository contains pretrained text2asmr model files, audio files and training+inference notebooks. |
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## Dataset Details |
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This unique dataset is tailored for training and deploying text-to-speech (TTS) systems specifically focused on ASMR (Autonomous Sensory Meridian Response) content. It includes a comprehensive collection of pretrained model files, audio files and training code suitable for TTS applications. |
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### Dataset Description |
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Inside this dataset, you shall find zipped folders as is follows: |
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1. **wavs_original:** original wav files as it was converted from the original video |
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2. **wavs:** original wav files broken into 1 minute chunks |
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3. **transcripts_original:** transribed scripts of the original wav files |
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4. **transcripts:** transribed scripts of the files in wav folder |
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5. **models:** text to spectrogram model trained on Glow-TTS |
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6. **ljspeech:** alignment files and respective checkpoint models (text to phoneme) |
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7. **transformer_tts_data.ljspeech**: trained checkpoint models and other files |
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And the following files: |
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1. **Glow-TTS.ipynb:** Training and inference code for GlowTTS models |
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2. **TransformerTTS.ipynb:** Training and inference code for Transformer models |
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3. **VITS_TTS.ipynb:** Optional code for training VITS models; follows the same format as GlowTTS |
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4. **metadata_original.csv:** ljspeech formatted transcriptions of wav_original folder; ready for TTS training |
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5. **metadata.csv:** ljspeech formatted transcriptions of wav folder; ready for TTS training |
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# Latest Update: End-To-End TEXT-2-ASMR with Diffusion |
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Based on the paper, **E3 TTS: EASY END-TO-END DIFFUSION-BASED TEXT TO SPEECH** |
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(Yuan Gao, Nobuyuki Morioka, Yu Zhang, Nanxin Chen) Google |
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A text-to-asmr UNet-Diffusion model differing slightly from the framework mentioned in the paper was trained on the same audio-transcript paired dataset for 1000DDPM and 10 epochs. |
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Model metrics: |
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1. General Loss: 0.000134 |
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2. MSE Loss: 0.000027 |
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3. RMSE Loss: 0.000217 |
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4. MAE Loss: 0.000018 |
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- **Curated by:** Alosh Denny, Anish S |
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- **Language(s) (NLP):** English |
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- **License:** MIT |
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### Dataset Sources |
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**Youtube:** Rebeccas ASMR, Nanou ASMR, Gibi ASMR, Cherie Lorraine ASMR, etc. |
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## Uses |
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The dataset can be used to train text2spec2mel, text2wav, and/or other end-to-end text-to-speech models. |
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### Direct Use |
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Pretrained models can be tested out with the TransformerTTS notebook and the Glow-TTS notebook. |
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## Dataset Card Authors |
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Alosh Denny, Anish S |
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## Dataset Card Contact |
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[email protected] |
