Text to speech is the generation of speech synthesized from the text. The technology is used to communicate with users when reading a screen is not possible or impractical. This not only opens up apps and information to use in new ways but can also make the world more accessible to people who cannot read text on a screen. In this article, I will take you through building your TTS with Python.
The technology behind the TTS has evolved over the past few decades. Using natural language processing, it is now possible to produce very natural speech that includes changes in pitch, speed, pronunciation and inflexion.
Text to Speech with Python
I will simply start with importing all the necessary libraries that we need for this task to create a program that takes the text of an article online and converts it into speech:
#Import the libraries from newspaper import Article import nltk from gtts import gTTS import osCode language: Python (python)
Now, if you have face any error in importing the libraries, then you must have not installed any of these libraries. You can easily install any library in python, by writing a very simple command in your terminal – pip install package name. Now after installing and importing the libraries, we need to get an article from online sources so that we can create a program to convert text to speech from that article:
#Get the article article = Article('https://hackernoon.com/future-of-python-language-bright-or-dull-uv41u3xwx')Code language: Python (python)
Now, let’s download and parse the article:
Now you need to download the “punkt” package if you have already downloaded it before you can skip downloading it if you will still download it again, it will give you a reminder that it is already available in your system which will not harm anything. So now, I will download the punkt package and apply Natural Language processing on it:
nltk.download('punkt') article.nlp()Code language: Python (python)
Now, I will define a variable to store the article:
#Get the articles text mytext = article.textCode language: Python (python)
Now we have to choose the language of speech. Note “en” means English. You can also use “pt-br” for Portuguese and there are others:
language = 'en' #EnglishCode language: Python (python)
Now we need to pass the text and language to the engine to convert the text to speech and store it in a variable. Mark slow as False to tell the plug-in that the converted audio should be at high speed:
myobj = gTTS(text=mytext, lang=language, slow=False)Code language: Python (python)
Running Text to Speech Program
Now, we have converted the article for text-to-speech, so now the next step is to save this speech to mp3 file:
myobj.save("read_article.mp3")Code language: Python (python)
Now let’s play the converted audio file from text to speech in Windows, using the Windows command “start” followed by the name of the mp3 file:
os.system("start read_article.mp3")Code language: Python (python)
Also, Read – Fashion Recommendation System with Machine Learning.
I hope you liked this article on converting text to speech using python. Feel free to ask your valuable questions in the comments section below. You can also follow me on my Medium Publication to learn every topic of Machine Learning.
Also, Read – The Future of Machine Learning.
I read some your project in python and i am beginner in this .
the question what’s the software use in python ?
Google , pycharm ,visualstudio , ….etc
I see many software’s and i do not know which the best one for start learning
While you are creating an application you can use VS Code and when you are working on a data science task where you have to create a lot of data visualisation then you can use Google Colab or a Jupyter notebook.