Text to speech conversion (TTS) – webage.design

Text to speech conversion (TTS)
I recommend listening to this short audio clip or at least the first 30 seconds.
It’s not the subject matter of the clip that is important but the way the two characters (Jenny and Damon) were created.

The characters are actually robots and the video was generated by artificial intelligence software based on written text.
It’s actually a text-to-speech conversion, achieved using the cloud computing services platform, Microsoft Azure.
The result is promising and the application areas are diverse: podcasts, presentation videos, etc.
Those interested in the topic can contact me for information.
I can help/explain how you can generate such audio clips.
Email WhatsApp

Generalities about text-to-speech conversion.

Text-to-speech (TTS) is a technology that allows computers to convert written text into spoken words.
TTS systems are used in a variety of applications such as voice assistants, e-learning platforms and screen readers for the visually impaired.
In this article, we take a closer look at how TTS conversion works and the different approaches and tools available for generating speech from text.
There are several approaches to TTS conversion, each with their own strengths and limitations.
Rule-based systems use a set of predefined rules to convert text to speech. These rules can include phonetic rules for converting text into phonemes (the smallest units of sound in a language), prosodic rules for adding intonation and stress to speech, and syntactic rules for generating the appropriate word order and sentence structure.
Rule-based systems are relatively simple to implement and can produce good results for limited domains or languages. However, they can be inflexible and produce unnatural-sounding speech when rules are not followed exactly.
Statistical systems use large datasets of speech and recorded text to learn patterns and generate speech. These systems often use machine learning and natural language processing (NLP) techniques to analyse the relationship between text and corresponding speech.
Statistical systems can produce more natural-sounding speech than rule-based systems because they can adapt to variations in the data and generate speech that reflects patterns learned from the data. However, statistical systems may require a large amount of data and may not generalize well to new languages or domains.
Neural TTS systems use deep learning techniques to generate speech from text. These systems use artificial neural networks, which are modelled after the structure of the human brain, to learn the relationship between text and corresponding speech.
Neural TTS systems are generally considered to be the most accurate and natural, as they can model complex patterns and variations in data. However, they can require a large amount of data and computational resources to train and may not be suitable for real-time applications.
Many TTS software tools and services are available on the market, ranging from free and open-source to commercial products.
These tools often come with a variety of features and customization options, such as the ability to adjust the voice, pitch and speed of the speech generated or to choose from multiple languages and accents.

Examples of popular TTS tools and services:

Google Text-to-Speech:
This is a free TTS service offered by Google that can be used to generate speech from text in a variety of languages.
Amazon Polly:
Is a cloud-based TTS service offered by Amazon that allows users to generate speech from text in multiple languages and voices.
Nuance Communications:
Is a commercial TTS provider that offers a range of TTS products for various applications, including voice assistants, e-learning platforms and screen readers.
Is an open-source TTS software that can be used on a variety of platforms, including Linux, Windows and Android.

TTS systems have a wide range of applications, including:

Voice assistants:
TTS technology is widely used in voice assistants, such as Amazon’s Alexa and Google Assistant, to convert written text into spoken words. These systems use TTS to generate answers to user questions and commands, as well as provide information and assistance.
E-learning platforms:
TTS systems can be used in e-learning platforms to deliver audio versions of written content, such as textbooks and courses. This can be particularly useful for students with learning difficulties or who prefer to learn by listening.
Screen readers:
Screen readers are software programs that allow people with visual impairments to access information displayed on a computer screen. They do this by converting text on the screen into synthesised speech, which can be listened to through computer speakers or a connected headset.
Text-to-speech (TTS) technology is used by screen readers to synthesise speech from on-screen text.
The screen reader reads the text on the screen aloud, allowing the user to hear what is displayed. TTS technology has come a long way in recent years and can produce very natural-sounding speech, making it easier for people with visual impairments to use computers and access information online.

Leave a Reply

Your email address will not be published. Required fields are marked *