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  ---
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  Model Type: Text to Speech
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  Supported Languages: Assamese, Bengali, Bodo, Gujarati, Hindi, Kannada, Malayalam, Manipuri, Marathi, Odia, Punjabi, Rajasthani, Tamil, Telugu, Urdu
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  ---
 
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  ***Demo: [IITM-TTS Demo](https://iitm-tts.onrender.com) | This may take approximately 30 seconds to load the first time and will go idle after 15 minutes of inactivity.***
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  # Fastspeech2_HS_Flask_API
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  ```
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  Alternatively, you can download the models from the original repository [Fastspeech2_HS](https://github.com/smtiitm/Fastspeech2_HS)
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- and organize the folder structure as specified below. Skip this step if already cloned the repository from Hugging Face.
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-
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- ```bash
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- models
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- ├── hindi
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- │ ├── female
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- │ └── male
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- ├── tamil
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- │ ├── female
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- │ └── male
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- .
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- .
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- .
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- └── marathi
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- ├── female
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- └── male
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- ```
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-
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- ### Installation:
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-
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- Create a virtual environment and activate it:
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- ```bash
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- python3 -m venv tts-hs-hifigan
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- source tts-hs-hifigan/bin/activate
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- ```
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-
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- Install the required dependencies by running:
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- ```bash
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- pip install -r requirements.txt
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- ```
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-
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- ### Run Flask server:
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- Ensure the server application is running correctly before proceeding. Use the following commands and check for any errors:
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- ```bash
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- python3 flask_app.py
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- # OR
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- gunicorn -w 2 -b 0.0.0.0:5000 flask_app:app --timeout 600
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- ```
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-
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- If the application is running without any issues, proceed to start the server using the following command:
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- ```bash
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- bash start.sh
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- ```
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-
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- ### API
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- ```python
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- """
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- This is a sample API code to send a text to the server and recieve speech
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- for the given text.
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-
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- Supported languages:
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-
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- Assamese, Bengali, Bodo, Gujarati, Hindi, Kannada, Malayalam, Manipuri
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- Marathi, Odia, Punjabi, Rajasthani, Tamil, Telugu, Urdu
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-
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- """
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- import requests
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- import json
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- import base64
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-
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- # endpoint
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- url = "http://localhost:5000/tts"
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-
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- lang = 'hindi'
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- gender = 'female'
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- text = "सुप्रभात, आप कैसे हैं?" # hindi
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- # text = "സുപ്രഭാതം, സുഖമാ?" # malayalam
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- # text = "সুপ্ৰভাত, তুমি কেনে?" # manipuri
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- # text = "सुप्रभात, तुम्ही कसे आहात?" # marathi
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- # text = "ಶುಭೋದಯ, ನೀವು ಹೇಗಿದ್ದೀರಿ?" # kannada
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- # text = "बसु म्विथ्बो, बरि दिबाबो?" # bodo male yet to be added <---
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- # text = "Good morning, how are you?" # english
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- # text = "সুপ্ৰভাত, আপুনি কেমন আছে?" # assamese
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- # text = "காலை வணக்கம், நீங்கள் எப்படி இருக்கின்றீர்கள்?" # tamil
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- # text = "ସୁପ୍ରଭାତ, ଆପଣ କେମିତି ଅଛନ୍ତି?"
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- # text = "सुप्रभात, आप कैसे छो?" # rajasthani
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- # text = "శుభోదయం, మీరు ఎలా ఉన్నారు?" # telugu
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- # text = "সুপ্রভাত, আপনি কেমন আছেন?" # bengali
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- # text = "સુપ્રભાત, તમે કેમ છો?" # gujarati
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-
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- payload = json.dumps(
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- {
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- "input": text,
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- "gender": gender,
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- "lang": lang,
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- "alpha": 1 # to control speed
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- })
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-
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- headers = {'Content-Type': 'application/json'}
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- response = requests.request("POST", url, headers=headers, data=payload).json()
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-
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- # save the received encoded audio
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- audio = response['audio']
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- file_name = "tts.wav"
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- wav_file = open(file_name,'wb')
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- decode_string = base64.b64decode(audio)
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- wav_file.write(decode_string)
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- wav_file.close()
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- ```
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-
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- ### Citation for the original repo
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- If you use this Fastspeech2 Model in your research or work, please consider citing:
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-
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-
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- COPYRIGHT
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- 2023, Speech Technology Consortium,
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- Bhashini, MeiTY and by Hema A Murthy & S Umesh,
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- DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING
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- and
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- ELECTRICAL ENGINEERING,
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- IIT MADRAS. ALL RIGHTS RESERVED "
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-
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-
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- Shield: [![CC BY 4.0][cc-by-shield]][cc-by]
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-
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- This work is licensed under a
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- [Creative Commons Attribution 4.0 International License][cc-by].
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-
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- [![CC BY 4.0][cc-by-image]][cc-by]
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-
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- [cc-by]: http://creativecommons.org/licenses/by/4.0/
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- [cc-by-image]: https://i.creativecommons.org/l/by/4.0/88x31.png
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- [cc-by-shield]: https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey.svg
 
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  ---
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  Model Type: Text to Speech
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  Supported Languages: Assamese, Bengali, Bodo, Gujarati, Hindi, Kannada, Malayalam, Manipuri, Marathi, Odia, Punjabi, Rajasthani, Tamil, Telugu, Urdu
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  ---
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  ***Demo: [IITM-TTS Demo](https://iitm-tts.onrender.com) | This may take approximately 30 seconds to load the first time and will go idle after 15 minutes of inactivity.***
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  # Fastspeech2_HS_Flask_API
 
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  ```
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  Alternatively, you can download the models from the original repository [Fastspeech2_HS](https://github.com/smtiitm/Fastspeech2_HS)
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