The text reader software industry needs to adapt to the different variations of widely spoken languages in the world. Most popular companies have created unique custom voice personas for the English language. These voices are the best in terms of quality and authenticity.
However, there has been huge negligence when it comes to other popular languages in the world and their widely spoken accents and dialects. The demand to create voices that could be used by these people who speak these certain accents is expanding.
To understand the scarcity of different accent voices for a single language, we need to understand first how AI voices for primary languages are developed.
A synthetic voice is an artificially produced version of human speech. It is created in three stages. The first stage is text to words. It is a preprocessing method to reduce ambiguity on how a certain text is read.
The second stage is words to phonemes. In this part, a dictionary of words; is prebuilt to the computer; helps pronounce certain letters or phonemes, and reads the text.
The third stage is phonemes to sound. It allows a sequence of written words to be converted to a sequence of sounds that need speaking. Recordings of humans uttering the phonemes are then used and can reference basic sound frequencies to produce the sound.
There is a possibility for Text reader software to reflect and create multiple accents. Some of them have already developed English language variants.
It depends on how the voice is structured and the voice actors used to complete the recording. Most text-to-speech voices are created by linking a stream of individual phonemes in context.
These phonemes are registered by a professional voice actor uttering a script and then cut into sections.
Most professional voice actors who speak with an accent are likely to convey it to the voice. These voice synthesis companies will only create voices with specific accents or dialects if there was a demand or a one-off request by someone looking for that specific voice.
As we have seen in the previous section, English is usually the most requested language to have different variations. To reflect that, Mandarin Chinese is the most spoken language in the world.
Even though Mandarin Chinese is the most spoken language in the world, English is considered to be a global language since it is spoken and understood by almost every region of the world. But what about other widespread languages? Even variants are spoken by minorities?
Well, some might argue that variants spoken by minorities are not worthy to be produced simply because they won’t be used in a global business context. However, these voice technologies are only significant when used in their own context and within their own communities. They are even more paramount when used in a translation paradigm to widespread important information.
Furthermore, the real challenge here lies in coping with the endless variations of a single language. How to manage different regional accents to distinctive use of grammar and vocabulary. Few of these variations can even lead to confusion in communication between people speaking the same language.
Text reader software companies are in need to overcome these challenges and come up with operative and effective technology.
The need to serve all accents in the world is a must
It is required that Text-to voice developers break the linear and biased way in which they deal with variants and accents.
The current text-to-sound strategy is only going to work for one subset of the population. However, for someone who is dependent on these technologies and can only use their own dialect, being misunderstood when using an inadequate voice could have serious consequences.
There needs to be more inclusion and diversity among the creators and beta testers of these text reader software technologies. One way to do it is by testing their product on a more wide-scale and including diverse workforces so people from different backgrounds and perspectives can directly impact the requirements of speech technologies.
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