Text to speech (TTS) technology is increasingly developing, helping computers read text with a real human-like voice. In particular, Vietnamese TTS is an important field, helping to popularize technology in Vietnam. However, developing Vietnamese TTS also poses many challenges due to the characteristics of the language.
Vietnamese is an isolated language, each syllable is made up of one consonant and one or more vowels. The consonant and vowel system in Vietnamese is rich and diverse. This creates the biggest challenge in developing Vietnamese TTS, which is how to synthesize all syllables with good quality.
In addition, determining the tone (horizontal, hypocritical, sharp, asking, falling) also greatly affects the quality of reading voice. Word order in a sentence is also an important factor that determines the intonation and rhythm of the reading voice. Therefore, to create good Vietnamese TTS, it is necessary to solve phonological and grammatical problems well.
Currently, a number of large technology companies such as Google and Microsoft have been developing Vietnamese TTS based on deep learning technology. They use deep learning neural networks to simulate human speech in the most realistic way. However, the quality still has some limitations in terms of intonation and pronunciation.
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Many experts believe that to improve the quality of Vietnamese TTS, it is necessary to increase research on Vietnamese linguistics as well as collect more natural speech data. Besides, there needs to be separate assessment standards for Vietnamese trainees, consistent with language characteristics. Finally, collaboration between linguists and software engineers is also necessary.
Hopefully in the future, Vietnamese TTS technology will develop further, helping Vietnamese people more easily access information, bringing many practical values to life. This promises to be a breakthrough technology field for industry 4.0 in Vietnam in the near future.